In this paper, a Self-tuning Fuzzy PI controller is used for the supply air pressure Control
loop for Heating, Ventilation and Air-Conditioning (HVAC) system. The modern H. V. A. Cussing
direct digital control methods have provided useful performance data from the building occupants. The
self-tuning Fuzzy PI controller (STFPIC) adjusts the output scaling factor on-line by fuzzy rules in
accordance to the current trend of the control process. This research work has got the integration and
application of these fundamental sources of information, using some modern and novel techniques. In
Comparison to PID and Adaptive Neuro-Fuzzy (ANF) Controllers, the simulation results show that
STFPIC performances are better under normal conditions as well as extreme conditions where in the
HVAC system encounters large variations. The cost and scalability of the setechniques can be
positively influenced by the recent technological advancement in computing power, sensors and data
bases.
Distributed Control System Applied in Temperatur Control by Coordinating Mult...TELKOMNIKA JOURNAL
In Distributed Control System (DCS), multitasking management has been important issues
continuously researched and developed. In this paper, DCS was applied in global temperature control
system by coordinating three Local Control Units (LCUs). To design LCU’s controller parameters, both
analytical and experimental method were employed. In analytical method, the plants were firstly identified
to get their transfer functions which were then used to derive control parameters based on desired
response qualities. The experimental method (Ziegler-Nichols) was also applied due to practicable reason
in real industrial plant (less mathematical analysis). To manage set-points distributed to all LCUs, master
controller was subsequently designed based on zone of both error and set-point of global temperature
controller. Confirmation experiments showed that when using control parameters from analytical method,
the global temperature response could successfully follow the distributed set-points with 0% overshoot,
193.92 second rise time, and 266.88 second settling time. While using control parameters from
experimental method, it could also follow the distributed set-points with presence of overshoot (16.9%), but
has less rise time and settling time (111.36 and 138.72 second). In this research, the overshoot could be
successfully decreased from 16.9 to 9.39 % by changing master control rule. This proposed method can
be potentially applied in real industrial plant due to its simplicity in master control algorithm and presence
of PID controller which has been generally included in today industrial equipments.
Chapter 8 Pid controllers and modified pid controllers. From the book (Ogata Modern Control Engineering 5th).
8-1 introduction
8-2 Ziegler-Nichols rules for tuning pid controllers .
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Enhanced self-regulation nonlinear PID for industrial pneumatic actuatorIJECEIAES
The present article describes the improvement of Self-regulation Nonlinear PID (SN-PID) controller. A new function is introduced to improve the system performance in terms of transient without affecting the steady state performance. It is used to optimize the nonlinear function available on this controller. The signal error is reprocessed through this function, and the result is used to tune the nonlinear function of the controller. Furthermore, the presence of the dead zone on the proportional valve is solved using Dead Zone Compensator (DZC). Simulations and experiments were carried out on the pneumatic positioning system. Comparisons between the existing methods were examined and successfully demonstrated.
IRJET- Speed Control of Induction Motor using Hybrid PID Fuzzy ControllerIRJET Journal
This document presents a study on using a hybrid PID fuzzy controller with a BAT optimization algorithm to control the speed of an induction motor. It begins with background on PID controllers and fuzzy logic controllers. It then proposes using a BAT algorithm to select the Kp and Ki parameters of a PI controller to regulate motor speed. The results show that the proposed BAT-PID controller reduces speed fluctuations and settling time compared to a traditional PID controller. In conclusion, the hybrid fuzzy-PID controller with BAT optimization improves induction motor speed control.
This document discusses bioreactor control systems. It describes different types of control systems including manual control, automatic control, two-position controllers, proportional control, integral control, and derivative control. It explains that automatic control systems use four basic components: a measuring element, controller, final control element, and the process to be controlled. The document also summarizes different combinations of control methods, such as proportional plus integral control and proportional plus integral plus derivative control.
Speed control of dc motor using fuzzy pid controller-mid term progress reportBinod kafle
This document presents a speed control system for a DC motor using a PID fuzzy controller. It discusses modeling the DC motor, tuning the PID controller using Ziegler-Nichols and auto-tuning methods in MATLAB, and comparing the performance of the two tuning approaches. The work completed includes simulating the motor speed control using a conventional PID controller. Remaining work involves defining fuzzy logic membership functions and rules, implementing fuzzy-PID control in MATLAB simulations, and comparing its performance to conventional PID control.
Comparison of Tuning Methods of PID Controllers for Non-Linear Systempaperpublications3
Abstract: Modern days have seen vast developments in the field of controller’s .There are various controllers developed these days with various different specifications. But the only drawback is that, there is no fixed method for the tuning of these controllers, which is necessary for controlling of the system based on the variation of the input or for the changes in the system. In order to overcome this drawback, in this paper we have compared various tuning methods of PID controller for non-linear system. As a non-linear system we have taken the dc motor as a system. For the particular DC motor controller transfer function has been determined and control parameters such as Proportional Gain, Integral Time and Derivative time are identified. They are numerous methods of developing a Proportional Integral and Derivative (PID) Controller, amongst them some methods are adopted in this paper and Comparisons of Time Domain specifications of those controllers has been carried out.
Distributed Control System Applied in Temperatur Control by Coordinating Mult...TELKOMNIKA JOURNAL
In Distributed Control System (DCS), multitasking management has been important issues
continuously researched and developed. In this paper, DCS was applied in global temperature control
system by coordinating three Local Control Units (LCUs). To design LCU’s controller parameters, both
analytical and experimental method were employed. In analytical method, the plants were firstly identified
to get their transfer functions which were then used to derive control parameters based on desired
response qualities. The experimental method (Ziegler-Nichols) was also applied due to practicable reason
in real industrial plant (less mathematical analysis). To manage set-points distributed to all LCUs, master
controller was subsequently designed based on zone of both error and set-point of global temperature
controller. Confirmation experiments showed that when using control parameters from analytical method,
the global temperature response could successfully follow the distributed set-points with 0% overshoot,
193.92 second rise time, and 266.88 second settling time. While using control parameters from
experimental method, it could also follow the distributed set-points with presence of overshoot (16.9%), but
has less rise time and settling time (111.36 and 138.72 second). In this research, the overshoot could be
successfully decreased from 16.9 to 9.39 % by changing master control rule. This proposed method can
be potentially applied in real industrial plant due to its simplicity in master control algorithm and presence
of PID controller which has been generally included in today industrial equipments.
Chapter 8 Pid controllers and modified pid controllers. From the book (Ogata Modern Control Engineering 5th).
8-1 introduction
8-2 Ziegler-Nichols rules for tuning pid controllers .
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Enhanced self-regulation nonlinear PID for industrial pneumatic actuatorIJECEIAES
The present article describes the improvement of Self-regulation Nonlinear PID (SN-PID) controller. A new function is introduced to improve the system performance in terms of transient without affecting the steady state performance. It is used to optimize the nonlinear function available on this controller. The signal error is reprocessed through this function, and the result is used to tune the nonlinear function of the controller. Furthermore, the presence of the dead zone on the proportional valve is solved using Dead Zone Compensator (DZC). Simulations and experiments were carried out on the pneumatic positioning system. Comparisons between the existing methods were examined and successfully demonstrated.
IRJET- Speed Control of Induction Motor using Hybrid PID Fuzzy ControllerIRJET Journal
This document presents a study on using a hybrid PID fuzzy controller with a BAT optimization algorithm to control the speed of an induction motor. It begins with background on PID controllers and fuzzy logic controllers. It then proposes using a BAT algorithm to select the Kp and Ki parameters of a PI controller to regulate motor speed. The results show that the proposed BAT-PID controller reduces speed fluctuations and settling time compared to a traditional PID controller. In conclusion, the hybrid fuzzy-PID controller with BAT optimization improves induction motor speed control.
This document discusses bioreactor control systems. It describes different types of control systems including manual control, automatic control, two-position controllers, proportional control, integral control, and derivative control. It explains that automatic control systems use four basic components: a measuring element, controller, final control element, and the process to be controlled. The document also summarizes different combinations of control methods, such as proportional plus integral control and proportional plus integral plus derivative control.
Speed control of dc motor using fuzzy pid controller-mid term progress reportBinod kafle
This document presents a speed control system for a DC motor using a PID fuzzy controller. It discusses modeling the DC motor, tuning the PID controller using Ziegler-Nichols and auto-tuning methods in MATLAB, and comparing the performance of the two tuning approaches. The work completed includes simulating the motor speed control using a conventional PID controller. Remaining work involves defining fuzzy logic membership functions and rules, implementing fuzzy-PID control in MATLAB simulations, and comparing its performance to conventional PID control.
Comparison of Tuning Methods of PID Controllers for Non-Linear Systempaperpublications3
Abstract: Modern days have seen vast developments in the field of controller’s .There are various controllers developed these days with various different specifications. But the only drawback is that, there is no fixed method for the tuning of these controllers, which is necessary for controlling of the system based on the variation of the input or for the changes in the system. In order to overcome this drawback, in this paper we have compared various tuning methods of PID controller for non-linear system. As a non-linear system we have taken the dc motor as a system. For the particular DC motor controller transfer function has been determined and control parameters such as Proportional Gain, Integral Time and Derivative time are identified. They are numerous methods of developing a Proportional Integral and Derivative (PID) Controller, amongst them some methods are adopted in this paper and Comparisons of Time Domain specifications of those controllers has been carried out.
Nonlinear multivariable control and performance analysis of an air-handling unitAli Abedi
This document summarizes a study that investigates nonlinear control approaches for an air-handling unit (AHU). A nonlinear multi-input multi-output dynamic model of an AHU is developed. Both indoor temperature and relative humidity are controlled by manipulating air and cold water flow rates. Two nonlinear control approaches, gain scheduling and feedback linearization, are designed and compared. Results show feedback linearization achieves faster tracking of setpoints but with more overshoot, while gain scheduling has less oscillation in control inputs and likely lower energy use. Feedback linearization is also more robust to model parameter uncertainty.
On the fragility of fractional-order PID controllers for FOPDT processesISA Interchange
This paper analyzes the fragility issue of fractional-order proportional-integral-derivative controllers applied to integer first-order plus-dead-time processes. In particular, the effects of the variations of the controller parameters on the achieved control system robustness and performance are investigated. Results show that this kind of controllers is more fragile with respect to the standard proportional-integral-derivative controllers and therefore a significant attention should be paid by the user in their tuning.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of a new PID controller using predictive functional control optimizati...ISA Interchange
An improved proportional integral derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers.
This document provides an overview of PID controllers, including:
- The three components of a PID controller are proportional, integral, and derivative terms.
- PID controllers are widely used in industrial control systems due to their general applicability even without a mathematical model of the system.
- Ziegler-Nichols tuning rules can be used to experimentally determine initial PID parameters to provide a stable initial response for the system. Fine-tuning is then used to optimize the response.
Speed Control of DC Motor using PID FUZZY Controller.Binod kafle
speed control of separately excited dc motor using fuzzy PID controller(FLC).In this research, speed of separately excited DC motor is controlled at 1500 RPM using two approaches i.e. PSO PID and fuzzy logic based PID controller. A mathematical model of system is needed for PSO PID while knowledge based rules obtained via experiment required for fuzzy PID controller . The conventional PID controller parameters are obtained using PSO optimization technique. The simulation is performed using the in-built toolbox from MATLAB and output response are analyzed. The tuning of fuzzy PID uses simple approach based on the rules proposed and membership function of the fuzzy variables. Design specification of fuzzy logic controller (FLC) requires fuzzification, rule list and defuzzification process. The FLC has two input and three output. Inputs are the speed error and rate of change in speed error. The corresponding outputs are Kp, Ki and Kd. There are 25 fuzzy based rule list. FLC uses mamdani system which employs fuzzy sets in consequent part. The obtained result is compared on the basis of rise time, peak time, settling time, overshoot and steady state error. PSO PID controller has fast response but slightly greater overshoot whereas fuzzy PID controller has sluggish response but low overshoot. The selection can be done on the basis of system properties and working environment conditions. PSO PID can be used where the response desired is fast like robotics where as fuzzy PID can be used where desired operation is smooth like industries.
Automation refers to the use of machines and equipment to perform tasks that were previously done by humans. It is used in manufacturing to increase productivity, quality, and reduce costs. Some key benefits of automation include improved quality, reduced labor costs, increased speed and accuracy, and improved worker safety. Potential downsides include high upfront capital costs, high maintenance costs, risk of job losses, and reliance on continuous power supply. Automation can be applied at different stages of production like material handling, production processes, and quality inspection. The pharmaceutical industry uses automation for purposes like ensuring batch quality, consistency, compliance with standards, and handling of hazardous substances.
Adaptive Control Machining systems,Adaptive Control,Where to use adaptive control? Application:Sources of variability in machining,Types of Adaptive controls,Operation of ACC system,Relationship of AC software to APT program,Benefits of AC
Chapter 1 basic components of control systemHarish Odedra
This presentation is on basic of control engineering subject which is offered to 5th sem Mechanical Engineering Department in Gujarat Technological University.
A PID Controller with Anti-Windup Mechanism for Firminga Carbon SteelIJERA Editor
In this Paper, a classical PID controller with anti-windup technique is employed for controlling the
microstructure development during hot working process. The strength of any material is dependent on the grain
size of that material [4], [9]. The strength of the material is increased when its grain size is reduced. In this
paper, the standard Arrehenious equation of 0.3% carbon steel is utilized to obtain an optimal deformation path
such that the grain size of the product should be 26m. The 0.3% carbon steel improves in the machinability
by heat treatment [8]. It must also be noted that this steel is especially adaptable for machining or forging and
where surface hardness is desirable. The plant model is developed with grain size. The effect of process control
parameters such as strain, strain rate, and temperature on important microstructural features can be
systematically formulated and then solved as an optimal control problem. These approaches are applied to
obtain the desired grain size of 26m from an initial grain size of 180m. The simulation is done on various
grain sizes using the controller by MATLAB simulink toolbox. From the response it is found that the PID
controller with anti-windup provides better performance. Resulting tabulated performance indices showed a
considerable improvement in settling time besides reducing steady state error.
This document provides an introduction to process control. It defines a process as an operation that transforms raw materials into a more useful state. The objectives of process control are to produce desired outputs from inputs in the most economical way. Processes can be described by differential equations and are affected by various internal and external conditions. Effective process control requires maintaining safety, meeting production specifications, and optimizing economics while addressing changing external influences. Examples of processes include unit operations in chemical plants and manufacturing units. The document outlines the basic components of a process control system and loop.
The document discusses different types of controllers:
1) On-Off, P, PI, PD, and PID controllers. On-Off controllers have only two modes while P controllers use proportional gain. PI controllers add integral action to eliminate steady-state error. PD controllers use derivative action and PID controllers combine all three actions.
2) Block diagrams and transfer functions are presented to show how each controller type is modeled and its effect on the closed loop system. The proportional, integral, and derivative gains (Kp, Ki, Kd) determine each controller's effect.
3) PID controllers combine proportional, integral and derivative actions and are commonly used in industrial control systems due to their robust performance.
The Ziegler-Nichols tuning method is used to determine PID controller gains (Kp, Ki, Kd) based on the process model's stability point. The method involves:
1) Increasing Kp until the output oscillates at a frequency f0, defining the maximum gain Kmax.
2) Calculating gains using formulas based on Kmax and f0.
3) Applying the gains to a simulated hydraulic valve position control model, reducing steady state error and stabilizing the output. Further tuning can refine the gains.
This document provides an overview of control systems engineering. It discusses:
- The basics of control theory including open and closed loop control systems.
- Examples of control systems in real life including manual vs automatic control of a car.
- Classification of control systems as open loop or closed loop and the processes of each.
- Applications of control systems including temperature regulation and motor speed control.
- The purpose of control systems is to cause a system variable to conform to a desired value through feedback.
The document provides an introduction to process control. It defines process control and explains its importance in process industries. It discusses different types of processes like continuous, batch, and their characteristics. It also explains different process control elements like feedback, feedforward, manual and automatic control systems. It distinguishes between feedback and feedforward control schemes. It discusses different process variables involved in control like controlled, manipulated and disturbance variables. Finally, it explains concepts of process dynamics including different dynamic elements like resistance, capacitance, time constant, dead time, and their effect on process response.
The document discusses control systems and provides examples. It begins by describing the general process for designing a control system and examines examples throughout history. Modern control engineering includes strategies to improve manufacturing, energy efficiency, automobiles, and other applications. The document also discusses the gap between physical systems and their models in control system design and how an iterative process can effectively address this gap.
This document presents information on on-off controllers. It discusses that on-off controllers have only two output states - fully on or fully off. When the process variable exceeds the setpoint, the controller output switches fully on, and when it falls below the setpoint, the output switches fully off. This causes oscillations in the process variable. The document describes examples of on-off control schemes for fans, water heaters and water level. It also lists advantages like low cost and quick response, and disadvantages like inability to control systems with delays and lack of accuracy.
OPTIMIZING THE GREENHOUSE MICRO-CLIMATE MANAGEMENT BY THE INTRODUCTION OF ART...IAEME Publication
The socio-economic evolution of populations has in recent decades a rapid and multiple changes, including dietary habits that have been characterized by the consumption of fresh products out of season and widely available throughout the year.
Culture under shelters of fruit, vegetable and flower species developed from the classical to the greenhouse agro - industrial, currently known for its modernity and high level of automation (heating, misting, of conditioning, control, regulation and control, supervisor of computer etc.). New techniques have emerged, including the use of control devices and regulating climate variables in a greenhouse (temperature, humidity, CO2 concentration etc.) to the exploitation of artificial intelligence such as neural networks and / or fuzzy logic.
Simulating The Air-Condition Controlling In Operating Room And ImprovementWaqas Tariq
In this study we have tried necessary condition and suitable for air balance and temperature in the operating room, using a fuzzy expert controller system and thermal cameras are designed. Condition for implementation and simulation of this system has been studied to see if it can be true or not performed in hospitals. This is a completely new method, all the operating room by a fuzzy controller with thermal picture environment has been properly balanced to ventilation system work properly. Therefore, the operating room is simulated using MATLAB software so fuzzy control system is supposed to be shown the benefits of this control system. Input parameters of the system are important factors in determining the balance temperature and ambient temperature. The publication of these parameters is considered as an output parameter. By the expert system, an account statement with the membership functions for input parameters were defined. After classification of ventilation systems and related information, using a concept designed interface that with MATLAB software has been simulated, transferred to the computer and also whole system operation in the operating room during hundred minutes is shown. The results revealed by this controller showed that in terms of economic and reliability and other has more advantages than the previous single-phase system.
Nonlinear multivariable control and performance analysis of an air-handling unitAli Abedi
This document summarizes a study that investigates nonlinear control approaches for an air-handling unit (AHU). A nonlinear multi-input multi-output dynamic model of an AHU is developed. Both indoor temperature and relative humidity are controlled by manipulating air and cold water flow rates. Two nonlinear control approaches, gain scheduling and feedback linearization, are designed and compared. Results show feedback linearization achieves faster tracking of setpoints but with more overshoot, while gain scheduling has less oscillation in control inputs and likely lower energy use. Feedback linearization is also more robust to model parameter uncertainty.
On the fragility of fractional-order PID controllers for FOPDT processesISA Interchange
This paper analyzes the fragility issue of fractional-order proportional-integral-derivative controllers applied to integer first-order plus-dead-time processes. In particular, the effects of the variations of the controller parameters on the achieved control system robustness and performance are investigated. Results show that this kind of controllers is more fragile with respect to the standard proportional-integral-derivative controllers and therefore a significant attention should be paid by the user in their tuning.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Design of a new PID controller using predictive functional control optimizati...ISA Interchange
An improved proportional integral derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers.
This document provides an overview of PID controllers, including:
- The three components of a PID controller are proportional, integral, and derivative terms.
- PID controllers are widely used in industrial control systems due to their general applicability even without a mathematical model of the system.
- Ziegler-Nichols tuning rules can be used to experimentally determine initial PID parameters to provide a stable initial response for the system. Fine-tuning is then used to optimize the response.
Speed Control of DC Motor using PID FUZZY Controller.Binod kafle
speed control of separately excited dc motor using fuzzy PID controller(FLC).In this research, speed of separately excited DC motor is controlled at 1500 RPM using two approaches i.e. PSO PID and fuzzy logic based PID controller. A mathematical model of system is needed for PSO PID while knowledge based rules obtained via experiment required for fuzzy PID controller . The conventional PID controller parameters are obtained using PSO optimization technique. The simulation is performed using the in-built toolbox from MATLAB and output response are analyzed. The tuning of fuzzy PID uses simple approach based on the rules proposed and membership function of the fuzzy variables. Design specification of fuzzy logic controller (FLC) requires fuzzification, rule list and defuzzification process. The FLC has two input and three output. Inputs are the speed error and rate of change in speed error. The corresponding outputs are Kp, Ki and Kd. There are 25 fuzzy based rule list. FLC uses mamdani system which employs fuzzy sets in consequent part. The obtained result is compared on the basis of rise time, peak time, settling time, overshoot and steady state error. PSO PID controller has fast response but slightly greater overshoot whereas fuzzy PID controller has sluggish response but low overshoot. The selection can be done on the basis of system properties and working environment conditions. PSO PID can be used where the response desired is fast like robotics where as fuzzy PID can be used where desired operation is smooth like industries.
Automation refers to the use of machines and equipment to perform tasks that were previously done by humans. It is used in manufacturing to increase productivity, quality, and reduce costs. Some key benefits of automation include improved quality, reduced labor costs, increased speed and accuracy, and improved worker safety. Potential downsides include high upfront capital costs, high maintenance costs, risk of job losses, and reliance on continuous power supply. Automation can be applied at different stages of production like material handling, production processes, and quality inspection. The pharmaceutical industry uses automation for purposes like ensuring batch quality, consistency, compliance with standards, and handling of hazardous substances.
Adaptive Control Machining systems,Adaptive Control,Where to use adaptive control? Application:Sources of variability in machining,Types of Adaptive controls,Operation of ACC system,Relationship of AC software to APT program,Benefits of AC
Chapter 1 basic components of control systemHarish Odedra
This presentation is on basic of control engineering subject which is offered to 5th sem Mechanical Engineering Department in Gujarat Technological University.
A PID Controller with Anti-Windup Mechanism for Firminga Carbon SteelIJERA Editor
In this Paper, a classical PID controller with anti-windup technique is employed for controlling the
microstructure development during hot working process. The strength of any material is dependent on the grain
size of that material [4], [9]. The strength of the material is increased when its grain size is reduced. In this
paper, the standard Arrehenious equation of 0.3% carbon steel is utilized to obtain an optimal deformation path
such that the grain size of the product should be 26m. The 0.3% carbon steel improves in the machinability
by heat treatment [8]. It must also be noted that this steel is especially adaptable for machining or forging and
where surface hardness is desirable. The plant model is developed with grain size. The effect of process control
parameters such as strain, strain rate, and temperature on important microstructural features can be
systematically formulated and then solved as an optimal control problem. These approaches are applied to
obtain the desired grain size of 26m from an initial grain size of 180m. The simulation is done on various
grain sizes using the controller by MATLAB simulink toolbox. From the response it is found that the PID
controller with anti-windup provides better performance. Resulting tabulated performance indices showed a
considerable improvement in settling time besides reducing steady state error.
This document provides an introduction to process control. It defines a process as an operation that transforms raw materials into a more useful state. The objectives of process control are to produce desired outputs from inputs in the most economical way. Processes can be described by differential equations and are affected by various internal and external conditions. Effective process control requires maintaining safety, meeting production specifications, and optimizing economics while addressing changing external influences. Examples of processes include unit operations in chemical plants and manufacturing units. The document outlines the basic components of a process control system and loop.
The document discusses different types of controllers:
1) On-Off, P, PI, PD, and PID controllers. On-Off controllers have only two modes while P controllers use proportional gain. PI controllers add integral action to eliminate steady-state error. PD controllers use derivative action and PID controllers combine all three actions.
2) Block diagrams and transfer functions are presented to show how each controller type is modeled and its effect on the closed loop system. The proportional, integral, and derivative gains (Kp, Ki, Kd) determine each controller's effect.
3) PID controllers combine proportional, integral and derivative actions and are commonly used in industrial control systems due to their robust performance.
The Ziegler-Nichols tuning method is used to determine PID controller gains (Kp, Ki, Kd) based on the process model's stability point. The method involves:
1) Increasing Kp until the output oscillates at a frequency f0, defining the maximum gain Kmax.
2) Calculating gains using formulas based on Kmax and f0.
3) Applying the gains to a simulated hydraulic valve position control model, reducing steady state error and stabilizing the output. Further tuning can refine the gains.
This document provides an overview of control systems engineering. It discusses:
- The basics of control theory including open and closed loop control systems.
- Examples of control systems in real life including manual vs automatic control of a car.
- Classification of control systems as open loop or closed loop and the processes of each.
- Applications of control systems including temperature regulation and motor speed control.
- The purpose of control systems is to cause a system variable to conform to a desired value through feedback.
The document provides an introduction to process control. It defines process control and explains its importance in process industries. It discusses different types of processes like continuous, batch, and their characteristics. It also explains different process control elements like feedback, feedforward, manual and automatic control systems. It distinguishes between feedback and feedforward control schemes. It discusses different process variables involved in control like controlled, manipulated and disturbance variables. Finally, it explains concepts of process dynamics including different dynamic elements like resistance, capacitance, time constant, dead time, and their effect on process response.
The document discusses control systems and provides examples. It begins by describing the general process for designing a control system and examines examples throughout history. Modern control engineering includes strategies to improve manufacturing, energy efficiency, automobiles, and other applications. The document also discusses the gap between physical systems and their models in control system design and how an iterative process can effectively address this gap.
This document presents information on on-off controllers. It discusses that on-off controllers have only two output states - fully on or fully off. When the process variable exceeds the setpoint, the controller output switches fully on, and when it falls below the setpoint, the output switches fully off. This causes oscillations in the process variable. The document describes examples of on-off control schemes for fans, water heaters and water level. It also lists advantages like low cost and quick response, and disadvantages like inability to control systems with delays and lack of accuracy.
OPTIMIZING THE GREENHOUSE MICRO-CLIMATE MANAGEMENT BY THE INTRODUCTION OF ART...IAEME Publication
The socio-economic evolution of populations has in recent decades a rapid and multiple changes, including dietary habits that have been characterized by the consumption of fresh products out of season and widely available throughout the year.
Culture under shelters of fruit, vegetable and flower species developed from the classical to the greenhouse agro - industrial, currently known for its modernity and high level of automation (heating, misting, of conditioning, control, regulation and control, supervisor of computer etc.). New techniques have emerged, including the use of control devices and regulating climate variables in a greenhouse (temperature, humidity, CO2 concentration etc.) to the exploitation of artificial intelligence such as neural networks and / or fuzzy logic.
Simulating The Air-Condition Controlling In Operating Room And ImprovementWaqas Tariq
In this study we have tried necessary condition and suitable for air balance and temperature in the operating room, using a fuzzy expert controller system and thermal cameras are designed. Condition for implementation and simulation of this system has been studied to see if it can be true or not performed in hospitals. This is a completely new method, all the operating room by a fuzzy controller with thermal picture environment has been properly balanced to ventilation system work properly. Therefore, the operating room is simulated using MATLAB software so fuzzy control system is supposed to be shown the benefits of this control system. Input parameters of the system are important factors in determining the balance temperature and ambient temperature. The publication of these parameters is considered as an output parameter. By the expert system, an account statement with the membership functions for input parameters were defined. After classification of ventilation systems and related information, using a concept designed interface that with MATLAB software has been simulated, transferred to the computer and also whole system operation in the operating room during hundred minutes is shown. The results revealed by this controller showed that in terms of economic and reliability and other has more advantages than the previous single-phase system.
The Future of Air Conditioning & its Impact on the PlanetRishab Gupta
Air conditioning places a significant burden on energy systems and greenhouse gas emissions from air conditioners are projected to accelerate dramatically by 2050 as the number increases from 900 million to over 2.5 billion units worldwide. Improving the average efficiency of air conditioners globally by 30% by 2030 could reduce emissions by 25 billion metric tons of CO2 and reduce peak electricity demand significantly. While air conditioning provides health and productivity benefits, it is also a major contributor to global warming through greenhouse gas emissions. Regulations and development of more environmentally friendly cooling technologies must continue to address this challenge.
This 4-week industrial training report document provides an introduction, index, and acknowledgements section. It discusses refrigeration and air conditioning topics including methods of refrigeration, units of refrigeration, vapor compression refrigeration system components, and applications of refrigeration. The document is submitted to fulfill requirements for a diploma in mechanical engineering. It is comprised of 3 sentences or less.
Design of Neural Network Controller for Active Vibration control of Cantileve...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
A helicopter is an aircraft that is lifted and propelled by one or more horizontal rotors, each
consisting of two or more rotor blades. The main objective of this seminar topic is to study the basic
concepts of helicopter aerodynamics. The forces acting on helicopter i.e. lift, drag, thrust and weight
are considered for developing analytic equations. The main topics that are discussed include blade
motions like blade flapping, feathering and lead-lag. The effect of stall on helicopter blade flapping is
studied and it was noticed that there is a sudden lift drop at this stall condition. It was also found that
dynamic stall occurs due to rapidly changing angle of attack, which inturn affect the air flow over the
airfoil. Blade flapping angle and induced angle of attack are the main parameters concerned with stall.
The theory behind blade element analysis has been inferred in detail. The importance of all these in the
present scenario are also taken into consideration
Complex test pattern generation for high speed fault diagnosis in Embedded SRAMIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Resolution of human arm redundancy in point tasks by synthesizing two criteriaIJMER
The human arm is kinematically redundant in the task of pointing. As a result, multiple arm
configurations can be used to complete a pointing task in which the tip of the index finger is brought to a
preselected point in a 3D space. The authors have developed a four degrees of freedom (DOF)model of the
human arm with synthesis of two redundancy resolution criteria that were developed as an analytical tool
for studying the positioning tasks. The two criteria were: (1) minimizing the angular joint displacement
(Minimal Angular Displacement - MAD) and (2) averaging the limits of the shoulder joint range (Joint
Range Availability - JRA). As part of the experimental protocol conducted with ten subjects, the kinematics
of the human arm was acquired with a motion capturing system in a 3D space. The redundant joint angles
predicted by a equally weighted model synthesizing the MAD and JRA criteria resulted with a linear
correlation with the experimental data (slope=0.88; offset=1⁰; r
2=0.52). Given the experiment protocol,
individual criterion showed weaker correlation with experimental data (MAD slope=0.57, offset=14⁰,
r
2=0.36 or JRA slope=0.84, offset=-1⁰, r
2=0.45). Solving the inverse kinematics problem of articulated
redundant serials mechanism such as a human or a robotic arm has applications in fields of human-robot
interaction and wearable robotics, ergonomics, and computer graphics animation.
This document summarizes a study that used finite element analysis to analyze the impact performance of car bumpers made from two different materials - ABS plastic and polyether imide (PEI) - at varying speeds. The bumper design was modeled in Pro/Engineer and analyzed in SolidWorks. The results show that ABS plastic performed better than PEI, with lower stress, displacement, and strain values across speeds of 48 km/h and 75 km/h, indicating it has better impact resistance.
This document describes a Trust-Aware Routing Framework (TARF) designed to secure multi-hop routing in wireless sensor networks against attacks that misdirect traffic by replaying routing information to spoof identities. TARF evaluates the trustworthiness of neighboring nodes based on their past performance in delivering packets to the base station. It identifies untrustworthy or compromised nodes and routes data along paths that avoid those nodes, improving throughput. TARF requires neither tight time synchronization nor location information. Evaluation shows it effectively counters attacks using replayed routing data and maintains performance under dynamic network conditions.
This document summarizes and analyzes several signcryption schemes based on elliptic curves. Signcryption allows for both encryption and digital signing to be performed in one logical step, reducing computational costs compared to traditional signature-then-encryption schemes. The document analyzes schemes by Zheng and Imai, Bao & Deng, Gamage et al, and Jung et al in terms of security goals achieved, communication overhead, and computational costs. It finds that while all schemes achieve confidentiality, integrity, and unforgeability, they differ in supporting features like forward secrecy and public verification. The Zheng & Imai scheme has the lowest computational costs but lacks forward secrecy and public verification.
This document summarizes research on edge coloring of complement fuzzy graphs. It defines fuzzy graphs and complement fuzzy graphs. It presents an algorithm to find the complement of any fuzzy graph in O(n2) time. It then defines a coloring function based on α-cut to color the edges of the complement fuzzy graph. The paper provides an example of a fuzzy graph G, calculates its complement Gc, and uses the coloring function to find the chromatic number of Gc in 3 or fewer colors.
Contra * Continuous Functions in Topological SpacesIJMER
This document discusses contra α* continuous functions between topological spaces. It begins by introducing α*-open sets and various related concepts like α*-continuity. It then defines a function from one topological space to another to be contra α*-continuous if the preimage of every open set is α*-closed in the domain space. Some properties of contra α*-continuous functions are established, including that every contra-continuous function is contra α*-continuous. Examples are given to show the concepts are independent. The discussion considers the relationships between contra α*-continuity and other variations of contra-continuity.
Thermal Expansivity Behavior and Determination of Density of Al 6061-Sic-Gr ...IJMER
Metal Matrix Composites (MMCs) covers a very wide range of materials to simple
reinforcements of castings with low cost refractory wool, to complex continuous fires lay
Upgrading of Low Temperature Solar Heat with Cascade Vapor Compression and Ab...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
MCDM Techniques for the Selection of Material Handling Equipment in the Autom...IJMER
This document discusses different multi-criteria decision making (MCDM) techniques for selecting material handling equipment in the automobile industry. It first provides background on material handling and the automobile industry. It then reviews literature on relevant criteria for equipment selection: material, move, and method. The document proceeds to describe four MCDM techniques in detail: Analytic Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and provides numerical examples of applying each technique to different shops (body, paint, trim, final assembly) to determine the best material handling equipment.
Abstract: In this paper, we define and study about a new type of generalized closed set called, g∗s-closed set.Its relationship with already defined generalized closed sets are also studied
Illustration Clamor Echelon Evaluation via Prime Piece PsychotherapyIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Low Cost Self-assistive Voice Controlled Technology for Disabled PeopleIJMER
The document describes a proposed voice-controlled wheelchair and home automation system for disabled individuals. The system uses a microcontroller connected to a voice recognition module to recognize spoken commands. The commands control the motion of an electric wheelchair and operation of home appliances like lights. The system was tested for accuracy of wheelchair motion and home appliance control in response to voice commands, achieving 80% accuracy in a silent environment. The goal is to allow disabled people to control a wheelchair and home devices independently using only their voice.
A Novel Acknowledgement based Intrusion Detection System for MANETsIJMER
In Mobile Ad Hoc Networks(MANETs), a set of interacting nodes should cooperatively
implement the routing functions to enable end-to-end communication along dynamic paths composed by
multi-hop wireless links. Several multi-hop routing protocols have been proposed for ad hoc networks,
and most popular ones include: Dynamic Source Routing (DSR), Optimized Link-State Routing (OLSR),
Ad Hoc On-Demand Distance Vector (AODV) and Destination- Sequenced Distance-Vector (DSDV).
Most of these protocols rely on the assumption of a trustworthy cooperation among all participating
nodes; unfortunately, this may not be a realistic assumption in real hosts. Malicious hosts could exploit
the weakness of MANET to launch various kinds of attacks. Node mobility on ad hoc network cannot be
restricted. As results, many Intrusion Detection System(IDS) solutions have been proposed for the wired
network, which they are defined on strategic points such as switches, gateways, and routers, can not be
implemented on the MANET. Thus, the wired network IDS characteristics must be modified prior to be
implemented in the ad hoc network. Thus an IDS should be added to enhance the security level of
MANETs. If MANET can detect the attackers as soon as they enter the network, we will be able to
completely eliminate the potential vulnerabilities caused by compromised nodes at the first time. IDSs
usually act as the second layer in MANETs. This paper presents an novel IDS for MANETs which is
based on acknowledgements.
MODEL BASED ANALYSIS OF TEMPERATURE PROCESS UNDER VARIOUS CONTROL STRATEGIES ...Journal For Research
This paper analyze the temperature process in an empirical model. From the empirical model the system behavior is determined by transfer function and the basic controller strategies Ziegler-Nichols & Cohen-Coon method are implemented in it. With these tuning methods the best control strategies are obtained at the final stage by interfacing the system with NI-myRIO kit.
This document compares the performance of PID and FOPID controllers for automatic voltage regulation (AVR) systems. It presents models for the components of an AVR system and describes integer and fractional order PID controllers. Classical tuning methods like Ziegler-Nichols and Cohen-Coon are discussed for PID tuning. Ziegler-Nichols type rules are presented for FOPID tuning. Simulation results show that a FOPID controller tuned by Ziegler-Nichols methods provides better performance than PID controllers tuned by Ziegler-Nichols or Cohen-Coon, with less overshoot, faster settling time, and reduced rise time.
Research, Development Intelligent HVAC Control System Using Fuzzy Logic Contr...theijes
The paper describes an automatic climate in offices, describes the principles of the automation equipment climate, considered air parameters described control algorithms were compared automation system PIDcontroller and using fuzzy logic controller is designed microclimate model in Mathlab program with a fuzzy logic controller.
Speed control of dc motor using relay feedback tuned piAlexander Decker
This document discusses speed control of a DC motor using different controller types, including a relay feedback tuned PI controller, fuzzy PI controller (FPIC), and self-tuned fuzzy PI controller (STFPIC). The FPIC and STFPIC are developed using fuzzy logic to overcome limitations of conventional PID controllers for nonlinear systems without an accurate mathematical model. An experimental setup is used to test the controllers' performance on a DC motor. Results show the model-independent STFPIC and FPIC controllers improve speed control performance compared to the relay-tuned PI controller.
Disturbance Rejection with a Highly Oscillating Second-Order Process, Part I...Scientific Review SR
This research paper aims at investigating disturbance rejection associated with a highly oscillating
second-order process. The PD-PI controller having three parameters are tuned to provide efficient rejection of a
step input disturbance input. Controller tuning based on using MATLAB control and optimization toolboxes.
Using the suggested tuning technique, it is possible to reduce the maximum time response of the closed loop
control system to as low as 0.0095 and obtain time response to the disturbance input having zero settling time.
The effect of the proportional gain of the PD-PI controller on the control system dynamics is investigated for a
gain ≤ 100. The performance of the control system during disturbance rejection using the PD -PI controller is
compared with that using a second-order compensator. The PD-PI controller is superior in dealing with the
disturbance rejection associated with the highly oscillating second-order process
This document presents a method for automatically tuning PID controllers using particle swarm optimization (PSO) algorithm. It describes PID controllers and common tuning methods like Ziegler-Nichols. It then provides an overview of PSO algorithm and how it can be applied to optimize PID parameters to minimize a performance index for a DC motor model. Simulation results show the PSO-tuned PID controller provides improved rise time, settling time and overshoot compared to Ziegler-Nichols tuning.
Optimal tuning of pid power system stabilizer in simulink environmentIAEME Publication
This document summarizes a research paper that proposes using an optimal tuning method based on the Ziegler-Nichols tuning rules to determine the parameters of a PID power system stabilizer (PSS) controller in a MATLAB/Simulink model. The paper models a single machine connected to an infinite bus system, adds a PID controller with PSS, and simulates the system under normal load conditions. Simulation results show that the Ziegler-Nichols method yields PID controller parameters that provide better dynamic performance compared to a conventional trial and error approach, with lower overshoot and shorter settling time. The proposed optimally tuned PID-PSS controller thus improves the stability and performance of the synchronous generator in the simulated power system.
Estimation of Air-Cooling Devices Run Time Via Fuzzy Logic and Adaptive Neuro...IRJET Journal
The document describes a study that uses fuzzy logic and adaptive neuro-fuzzy inference systems (ANFIS) to develop a system for predicting the optimal run time of air cooling devices. Fuzzy logic models were developed using temperature and door state as inputs and run time as the output. Three different membership functions were tested and the triangular function performed best. ANFIS combines fuzzy logic and neural networks and was able to more accurately predict run time compared to fuzzy logic alone. The developed models provide an efficient way to control air cooling device run times.
Iaetsd design of fuzzy self-tuned load frequency controller for power systemIaetsd Iaetsd
This document describes a self-tuning fuzzy controller designed for load frequency control (LFC) in a multi-machine power system. Conventional PID gains are first obtained using ant colony system optimization. These gains are then used to design fuzzy controller gains to solve the LFC problem under different loading conditions and non-linearities like generation rate constraints. The proposed self-tuning fuzzy controller is tested on a practical thermal and hydel power system and shown to perform better than conventional integral and ACS-PID controllers in dealing with system uncertainties and changing operating conditions.
This document describes a PID controller with self-tuning capabilities using fuzzy logic. It replaces the conventional PID controller in a chopper-fed DC motor drive system to improve performance. The PID gains (KP, KI, KD) are automatically tuned online by a fuzzy logic controller based on the error and change in error. This allows the PID gains to adapt as needed for different operating conditions. Simulation results showed the proposed self-tuning PID controller performed better than a conventional PID controller.
Optimized proportional integral derivative (pid) controller for the exhaust t...Ali Marzoughi
The document describes using particle swarm optimization (PSO) to optimize the parameters of a proportional-integral-derivative (PID) controller for controlling the exhaust temperature of a gas turbine system. A new performance criterion called the multipurpose performance criterion (MPPC) is proposed that allows control of overshoot, rise time, and settling time by adjusting a weighting factor. The PSO algorithm is used to optimize the PID parameters by minimizing the MPPC. Results show the PSO-PID controller optimized with MPPC performs better than a conventional PID controller at achieving optimal transient response for the gas turbine exhaust temperature control system.
Modeling and Control of MIMO Headbox System Using Fuzzy LogicIJERA Editor
The Headbox plays an important role in pulp supply system with sheet forming in paper making process. The air cushion headbox is a nonlinear & strong coupling system. In the air cushion headbox system there were two important parameters which include total head and the stock level for improving pulp product quality. These two parameters make this system MIMO output system so for this a decoupling controls strategy was required for interaction between these two control loops. In this paper fuzzy tuned PID control scheme is proposed for controlling the nonlinear control problem in air cushion headbox after the system being decoupled. An attempt has been made for comparison between classical (PID) and fuzzy tuned PID controller. It concludes that the fuzzy tuned PID controller is found most suitable for MIMO system in terms of obtaining steady state properties. The effects of disturbances are studied through computer simulation using Matlab/Simulink toolbox.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Optimal control of load frequency control power system based on particle swar...theijes
In this work, PSO is proposed to set the gains of PID controller for LFC in single power systems area. This work has very significant issue because of persistent and random change load through working of power system. The proposed algorithm offer fluent performance, stable, and fast convergence to target value. Simulation results using MATLAB R2015a demonstrate that the proposed controller has more efficient of dynamic performance, better convergence, fast response from the other methods depend on rise and settling time of frequency deviation.
Mathematical Modeling and Fuzzy Adaptive PID Control of Erection MechanismTELKOMNIKA JOURNAL
This paper describes an application of fuzzy adaptive PID controller to erection mechanism.
Mathematical model of erection mechanism was derived. Erection mechanism is driven by electrohydraulic
actuator system which is difficult to control due to its nonlinearity and complexity. Therefore fuzzy
adaptive PID controller was applied to control the system. Simulation was performed in Simulink software
and experiment was accomplished on laboratory equipment. Simulation and experiment results of erection
angle controlled by fuzzy logic, PID and fuzzy adaptive PID controllers were respectively obtained. The
results show that fuzzy adaptive PID controller can effectively achieve the best performance for erection
mechanism in comparison with fuzzy logic and PID controllers.
Fuzzy controlled mine drainage system based on embedded systemIRJET Journal
This document proposes a fuzzy logic controlled mine drainage system based on an embedded system. Mines require proper drainage to improve stability, safety, and prevent equipment corrosion, but the variables involved like water levels and flow rates are unpredictable and non-linear, making an accurate empirical model difficult to design. The proposed system combines fuzzy logic control with an embedded system. Fuzzy logic handles the uncertainties while the embedded system provides better control, flexibility, compactness and user-friendliness. Sensors monitor water levels, flow rates, temperature, humidity and pressure, sending data to an operator. A fuzzy logic controller uses the sensor data and fuzzy rules to determine the number of pumps to operate, providing improved drainage control over traditional methods.
Improving Structural Limitations of Pid Controller For Unstable ProcessesIJERA Editor
PID controllers have structural limitations which make it impossible for a good closed-loop performance to be achieved. A step response with high overshoot and oscillations always results. In controlling processes with resonances, integrators and unstable transfer functions, the PI-PD controller provides a satisfactory closed-loop performance. In this paper, a simple approach to extracting parameters of a PI-PD controller from parameters of the conventional PID controller is presented so that a good closed-loop system performance is achieved. Simulated results from this formation are carried out to show the efficacy of the technique proposed.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Simulation analysis of Series Cascade control Structure and anti-reset windup...IOSR Journals
This document presents a simulation analysis of series cascade control structure and anti-reset windup technique for a jacketed continuous stirred tank reactor (CSTR). It discusses modeling and linearization of a CSTR process. It then analyzes series cascade control structure and designs PID controllers using auto-tuning. Next, it explains an anti-reset windup protection technique to address issues like overshoot and windup. Simulation results showing step responses indicate that responses with anti-windup have less overshoot and shorter settling time compared to the conventional cascade control system. In conclusion, the anti-reset windup technique improves closed-loop performance for the CSTR process.
Comparison of different controller strategies for Temperature controlIRJET Journal
This document compares different controller strategies (feedback, feedback with feedforward, and internal model control) for controlling temperature in a heat exchanger system. It describes a heat exchanger system with cold water input and temperature sensor output. The strategies are assessed based on transient response criteria like overshoot and settling time, and error-based criteria like integral of absolute and square errors. The study finds that internal model control outperforms the other strategies for a second-order plus dead time system.
Similar to Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller (20)
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
- Translucent concrete is a concrete based material with light-transferring properties,
obtained due to embedded light optical elements like Optical fibers used in concrete. Light is conducted
through the concrete from one end to the other. This results into a certain light pattern on the other
surface, depending on the fiber structure. Optical fibers transmit light so effectively that there is
virtually no loss of light conducted through the fibers. This paper deals with the modeling of such
translucent or transparent concrete blocks and panel and their usage and also the advantages it brings
in the field. The main purpose is to use sunlight as a light source to reduce the power consumption of
illumination and to use the optical fiber to sense the stress of structures and also use this concrete as an
architectural purpose of the building
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
A low cost automation system for removal of lint from cottonseed is to be designed and
developed. The setup consists of stainless steel drum with stirrer in which cottonseeds having lint is mixed
with concentrated sulphuric acid. So lint will get burn. This lint free cottonseed treated with lime water to
neutralize acidic nature. After water washing this cottonseeds are used for agriculter purpose
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
The incorporation of natural fibres such as munja fiber composites has gained
increasing applications both in many areas of Engineering and Technology. The aim of this study is to
evaluate mechanical properties such as flexural and tensile properties of reinforced epoxy composites.
This is mainly due to their applicable benefits as they are light weight and offer low cost compared to
synthetic fibre composites. Munja fibres recently have been a substitute material in many weight-critical
applications in areas such as aerospace, automotive and other high demanding industrial sectors. In
this study, natural munja fibre composites and munja/fibreglass hybrid composites were fabricated by a
combination of hand lay-up and cold-press methods. A new variety in munja fibre is the present work
the main aim of the work is to extract the neat fibre and is characterized for its flexural characteristics.
The composites are fabricated by reinforcing untreated and treated fibre and are tested for their
mechanical, properties strictly as per ASTM procedures.
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
Hybrid engine is a combination of Stirling engine, IC engine and Electric motor. All these 3 are
connected together to a single shaft. The power source of the Stirling engine will be a Solar Panel. The aim of
this is to run the automobile using a Hybrid engine
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
This document summarizes research on the fabrication and characterization of bio-composite materials using sunnhemp fibre. The document discusses how sunnhemp fibre was used to reinforce an epoxy matrix through hand lay-up methods. Various mechanical properties of the bio-composites were tested, including tensile, flexural, and impact properties. The results of the mechanical tests on the bio-composite specimens are presented. Potential applications of the sunnhemp fibre bio-composites are also suggested, such as in fall ceilings, partitions, packaging, automotive interiors, and toys.
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
The Greenstone belts of Karnataka are enriched in BIFs in Dharwar craton, where Iron
formations are confined to the basin shelf, clearly separated from the deeper-water iron formation that
accumulated at the basin margin and flanking the marine basin. Geochemical data procured in terms of
major, trace and REE are plotted in various diagrams to interpret the genesis of BIFs. Al2O3, Fe2O3 (T),
TiO2, CaO, and SiO2 abundances and ratios show a wide variation. Ni, Co, Zr, Sc, V, Rb, Sr, U, Th,
ΣREE, La, Ce and Eu anomalies and their binary relationships indicate that wherever the terrigenous
component has increased, the concentration of elements of felsic such as Zr and Hf has gone up. Elevated
concentrations of Ni, Co and Sc are contributed by chlorite and other components characteristic of basic
volcanic debris. The data suggest that these formations were generated by chemical and clastic
sedimentary processes on a shallow shelf. During transgression, chemical precipitation took place at the
sediment-water interface, whereas at the time of regression. Iron ore formed with sedimentary structures
and textures in Kammatturu area, in a setting where the water column was oxygenated.
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
In this paper, the mechanical characteristics of C45 medium carbon steel are investigated
under various working conditions. The main characteristic to be studied on this paper is impact toughness
of the material with different configurations and the experiment were carried out on charpy impact testing
equipment. This study reveals the ability of the material to absorb energy up to failure for various
specimen configurations under different heat treated conditions and the corresponding results were
compared with the analysis outcome
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
Robot guns are being increasingly employed in automotive manufacturing to replace
risky jobs and also to increase productivity. Using a single robot for a single operation proves to be
expensive. Hence for cost optimization, multiple guns are mounted on a single robot and multiple
operations are performed. Robot Gun structure is an efficient way in which multiple welds can be done
simultaneously. However mounting several weld guns on a single structure induces a variety of
dynamic loads, especially during movement of the robot arm as it maneuvers to reach the weld
locations. The primary idea employed in this paper, is to model those dynamic loads as equivalent G
force loads in FEA. This approach will be on the conservative side, and will be saving time and
subsequently cost efficient. The approach of the paper is towards creating a standard operating
procedure when it comes to analysis of such structures, with emphasis on deploying various technical
aspects of FEA such as Non Linear Geometry, Multipoint Constraint Contact Algorithm, Multizone
meshing .
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
This paper aims to do modelling, simulation and performing the static analysis of a go
kart chassis consisting of Circular beams. Modelling, simulations and analysis are performed using 3-D
modelling software i.e. Solid Works and ANSYS according to the rulebook provided by Indian Society of
New Era Engineers (ISNEE) for National Go Kart Championship (NGKC-14).The maximum deflection is
determined by performing static analysis. Computed results are then compared to analytical calculation,
where it is found that the location of maximum deflection agrees well with theoretical approximation but
varies on magnitude aspect.
In récent year various vehicle introduced in market but due to limitation in
carbon émission and BS Séries limitd speed availability vehicle in the market and causing of
environnent pollution over few year There is need to decrease dependancy on fuel vehicle.
bicycle is to be modified for optional in the future To implement new technique using change in
pedal assembly and variable speed gearbox such as planetary gear optimise speed of vehicle
with variable speed ratio.To increase the efficiency of bicycle for confortable drive and to
reduce torque appli éd on bicycle. we introduced epicyclic gear box in which transmission done
throgh Chain Drive (i.e. Sprocket )to rear wheel with help of Epicyclical gear Box to give
number of différent Speed during driving.To reduce torque requirent in the cycle with change in
the pedal mechanism
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIJMER
This document discusses integrating the Spring, Struts, and Hibernate frameworks to develop enterprise applications. It provides an overview of each framework and their features. The Spring Framework is a lightweight, modular framework that allows for inversion of control and aspect-oriented programming. It can be used to develop any or all tiers of an application. The document proposes an architecture for an e-commerce website that integrates these three frameworks, with Spring handling the business layer, Struts the presentation layer, and Hibernate the data access layer. This modular approach allows for clear separation of concerns and reduces complexity in application development.
Microcontroller Based Automatic Sprinkler Irrigation SystemIJMER
Microcontroller based Automatic Sprinkler System is a new concept of using
intelligence power of embedded technology in the sprinkler irrigation work. Designed system replaces
the conventional manual work involved in sprinkler irrigation to automatic process. Using this system a
farmer is protected against adverse inhuman weather conditions, tedious work of changing over of
sprinkler water pipe lines & risk of accident due to high pressure in the water pipe line. Overall
sprinkler irrigation work is transformed in to a comfortableautomatic work. This system provides
flexibility & accuracy in respect of time set for the operation of a sprinkler water pipe lines. In present
work the author has designed and developed an automatic sprinkler irrigation system which is
controlled and monitored by a microcontroller interfaced with solenoid valves.
On some locally closed sets and spaces in Ideal Topological SpacesIJMER
This document introduces and studies the concept of δˆ s-locally closed sets in ideal topological spaces. Some key points:
- A subset A is δˆ s-locally closed if A can be written as the intersection of a δˆ s-open set and a δˆ s-closed set.
- Various properties of δˆ s-locally closed sets are introduced and characterized, including relationships to other concepts like generalized locally closed sets.
- It is shown that a subset A is δˆ s-locally closed if and only if A can be written as the intersection of a δˆ s-open set and the δˆ s-closure of A.
- Theore
Intrusion Detection and Forensics based on decision tree and Association rule...IJMER
This paper present an approach based on the combination of, two techniques using
decision tree and Association rule mining for Probe attack detection. This approach proves to be
better than the traditional approach of generating rules for fuzzy expert system by clustering methods.
Association rule mining for selecting the best attributes together and decision tree for identifying the
best parameters together to create the rules for fuzzy expert system. After that rules for fuzzy expert
system are generated using association rule mining and decision trees. Decision trees is generated for
dataset and to find the basic parameters for creating the membership functions of fuzzy inference
system. Membership functions are generated for the probe attack. Based on these rules we have
created the fuzzy inference system that is used as an input to neuro-fuzzy system. Fuzzy inference
system is loaded to neuro-fuzzy toolbox as an input and the final ANFIS structure is generated for
outcome of neuro-fuzzy approach. The experiments and evaluations of the proposed method were
done with NSL-KDD intrusion detection dataset. As the experimental results, the proposed approach
based on the combination of, two techniques using decision tree and Association rule mining
efficiently detected probe attacks. Experimental results shows better results for detecting intrusions as
compared to others existing methods
Natural Language Ambiguity and its Effect on Machine LearningIJMER
This document discusses natural language ambiguity and its effect on machine learning. It begins by introducing different types of ambiguity that exist in natural languages, including lexical, syntactic, semantic, discourse, and pragmatic ambiguities. It then examines how these ambiguities present challenges for computational linguistics and machine translation systems. Specifically, it notes that ambiguity is a major problem for computers in processing human language as they lack the world knowledge and context that humans use to resolve ambiguities. The document concludes by outlining the typical process of machine translation and how ambiguities can interfere with tasks like analysis, transfer, and generation of text in the target language.
Today in era of software industry there is no perfect software framework available for
analysis and software development. Currently there are enormous number of software development
process exists which can be implemented to stabilize the process of developing a software system. But no
perfect system is recognized till yet which can help software developers for opting of best software
development process. This paper present the framework of skillful system combined with Likert scale. With
the help of Likert scale we define a rule based model and delegate some mass score to every process and
develop one tool name as MuxSet which will help the software developers to select an appropriate
development process that may enhance the probability of system success.
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersIJMER
The present study investigates the creep in a thick-walled composite cylinders made
up of aluminum/aluminum alloy matrix and reinforced with silicon carbide particles. The distribution
of SiCp is assumed to be either uniform or decreasing linearly from the inner to the outer radius of
the cylinder. The creep behavior of the cylinder has been described by threshold stress based creep
law with a stress exponent of 5. The composite cylinders are subjected to internal pressure which is
applied gradually and steady state condition of stress is assumed. The creep parameters required to
be used in creep law, are extracted by conducting regression analysis on the available experimental
results. The mathematical models have been developed to describe steady state creep in the composite
cylinder by using von-Mises criterion. Regression analysis is used to obtain the creep parameters
required in the study. The basic equilibrium equation of the cylinder and other constitutive equations
have been solved to obtain creep stresses in the cylinder. The effect of varying particle size, particle
content and temperature on the stresses in the composite cylinder has been analyzed. The study
revealed that the stress distributions in the cylinder do not vary significantly for various combinations
of particle size, particle content and operating temperature except for slight variation observed for
varying particle content. Functionally Graded Materials (FGMs) emerged and led to the development
of superior heat resistant materials.
Energy Audit is the systematic process for finding out the energy conservation
opportunities in industrial processes. The project carried out studies on various energy conservation
measures application in areas like lighting, motors, compressors, transformer, ventilation system etc.
In this investigation, studied the technical aspects of the various measures along with its cost benefit
analysis.
Investigation found that major areas of energy conservation are-
1. Energy efficient lighting schemes.
2. Use of electronic ballast instead of copper ballast.
3. Use of wind ventilators for ventilation.
4. Use of VFD for compressor.
5. Transparent roofing sheets to reduce energy consumption.
So Energy Audit is the only perfect & analyzed way of meeting the Industrial Energy Conservation.
An Implementation of I2C Slave Interface using Verilog HDLIJMER
This document describes the implementation of an I2C slave interface using Verilog HDL. It introduces the I2C protocol which uses only two bidirectional lines (SDA and SCL) for communication. The document discusses the I2C protocol specifications including start/stop conditions, addressing, read/write operations, and acknowledgements. It then provides details on designing an I2C slave module in Verilog that responds to commands from an I2C master and allows synchronization through clock stretching. The module is simulated in ModelSim and synthesized in Xilinx. Simulation waveforms demonstrate successful read and write operations to the slave device.
Discrete Model of Two Predators competing for One PreyIJMER
This paper investigates the dynamical behavior of a discrete model of one prey two
predator systems. The equilibrium points and their stability are analyzed. Time series plots are obtained
for different sets of parameter values. Also bifurcation diagrams are plotted to show dynamical behavior
of the system in selected range of growth parameter
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
1. International
OPEN ACCESS Journal
Of Modern Engineering Research (IJMER)
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 24|
Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller Mir Munawar Ali1, Mohd Aamer Khan2, Mohammed Shafi3, Mohd Abdul Omer Khan4, Md Azam Ali Farooky5, Syed Azam6 , Syed Khasim7, Shaik Wasei Eizaz Ahmed8 1 Associate Professor, Department of Electrical and Electronics Engineering, Deccan College of Engineering & Technology, Hyderabad, INDIA 2,3,4,5,6,7,8, Student ,Department of Mechanical Engineering , Sreyas Institute of Engineering & Technology, Nizam Institute of Engineering & Technology, Hyderabad, INDIA
I. Introduction Heating, Ventilation and Air-Conditioning (HVAC) systems require control of environmental variables such as pressure, temperature, humidity etc. In this system, the supply air pressure is regulated by the speed of a supply air fan. Increasing the fan speed will increase supply air pressure, and vice versa. In the large commercial buildings modern Direct Digital Control (D.D.C.) systems are becoming more favorable with the use of new sophisticated hardware. The H.V.A.C System components are used together and monitored remotely from a central location positions. The general trend in the design and commissioning of new commercial buildings includes the new types of these systems. It has been reported that fuzzy logic controller is very suitable for non- linear system and even with unknown structure. The tuning procedure can be a time-consuming, expensive and difficult task. This problem can be easily eliminated by using self-tuning scheme for fuzzy PI / PID controller. The conventional PID controllers are widely used in industry due to their simplicity in arithmetic, ease of using, good robustness, high reliability, stabilization and zero steady state error. But HVAC system is a non-linear and time variant system. It is difficult to achieve desired tracking control performance since tuning and self-adapting adjusting parameters on line are a scabrous problem of PID controller. In the first part of this paper Self-tuning Fuzzy Logic Controller is described. The second part described the implementation of the PI type Self-tuning Fuzzy Logic Controller on a HVAC system. In the last part simulation results are presented to compare with the well-tuned PID controller and Adaptive Neuro-Fuzzy (ANF) controller. II. Development of pi-Type self-Tuning Fuzzy controller The basic function of the rule base is to represent in a structured way the control policy of an experienced process operator and/or control engineer in the form of a set of production rules such as: If{process state}then{control output} Considered a set of desired input-output data pairs: [X1(1), X2(1); U (1)], [X1(2), X2(2); U (2)] ………. (1) Where X1 and X2 are inputs and u is the output. Here considered error(e)asX1and change of error(Δe)asX2.
Abstract: In this paper, a Self-tuning Fuzzy PI controller is used for the supply air pressure Control loop for Heating, Ventilation and Air-Conditioning (HVAC) system. The modern H. V. A. Cussing direct digital control methods have provided useful performance data from the building occupants. The self-tuning Fuzzy PI controller (STFPIC) adjusts the output scaling factor on-line by fuzzy rules in accordance to the current trend of the control process. This research work has got the integration and application of these fundamental sources of information, using some modern and novel techniques. In Comparison to PID and Adaptive Neuro-Fuzzy (ANF) Controllers, the simulation results show that STFPIC performances are better under normal conditions as well as extreme conditions where in the HVAC system encounters large variations. The cost and scalability of the setechniques can be positively influenced by the recent technological advancement in computing power, sensors and data bases.
2. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 25|
The task here is to generate as set of fuzzy rules from the desired input-output pairs of equation(1)through following steps[20]: Divide the input and output spaces into fuzzy regions. Assumed the domain interval so fx1,x2 and u are [x1−,x1+], [x2-,x2+]and[u−,u+]respectively. Fig.1 shows each domain interval divided into 7 equal regions, denoted by NB (negative big), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium) and PB (positive big) and assigns each region a fuzzy membership function. The shape of each membership function is triangular.
The term set so fe, Δe and u contains the same linguistic expressions for the magnitude part of the linguistic values ,i.e., LE =LΔE=LU={NB,NM,NS,ZE,PS,PM,PB} AsshowninFig.1andrepresents the rule base in the table formatasshowninTable1.Thecelldefinedbytheintersection ofthefirstrowandthefirstcolumnrepresentsarulesuchas,Ife(k)isNMandΔe(k)isPSthenu(k)isNS. The fuzzy controller is developedusingthis49fuzzyif-then rulesasshowninTable1.
3. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 26|
Similar like fuzzy controller, using symmetrical triangle calculate membership functions of (i)e, Δe, u(as shown in Fig.1) and (ii)gain updating factor(β) (as shown in Fig.2)for self-tuning mechanism. An addition al logic for addition at the output of controller is incorporated for PI controller. Because the discrete-time version equation of PI controller is
Δu(k)=KpΔe(k)+ KIe(k); Δu(k)=u(k)−u(k−1); or u(k) =Δu(k)+u(k−1), Where Δu(k) is the change of control output and u(k) is the total control output. Fig.3showsthattheoutputscaling-factor (SF) of the fuzzy controller is modified by a self-tuning mechanism, which is marked by bold rectangular portion in the figure. Then based on the knowledge of process control or by trial and error method choose suitable SF’s for inputs and output. The relationship as follows for PI type self- tuning fuzzy controller scheme. eN=Nee,ΔeN=NΔeΔe and Δu=(βNu)ΔuN Where Ne and NΔe are input scaling factor of error and change of error respectively and Nu is output scaling factor. There after apart from fuzzy PI controller rule determination, also determines the rule base for gain updating factor, in the similar way like, Ife is E and Δe is Δ E then β is β. A structure of which is shown in Table2, though it may vary. Further modification of the rule base for β may be required, depending on the type of response the control system designer wishes to achieve. AsshowninFig.3, when this β is multiplied with the fuzzy controller gain Nu, gives the overall gain of STFPIC. It is very important to note that the rule base for computation of β will always be dependent on the choice of the rule base for the controller. Choice of Scaling Factor (gain): The scaling factors also known as gains, which describe the particular input normalization and output demoralizations, plays an important role similar to that of the gain coefficients in a conventional controller. For example, a fuzzy controller can be represented as Nu∗u(k) =F(Ne∗e(k), NΔe∗Δe(k)), Where Ne, NΔ e and Nu are the scaling factors fore, Δ e and u respectively, and Fisanon linear function representing the fuzzy controller. Same gain principle is used in the design of self-tuning fuzzy controller.
4. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 27|
III. Simulation results A typical cooling only HVAC system is shown in Fig.8.In the system, the outside air is mixed with the building return air. Then the mixed air (supply air) is sucked through the cooling coil via a filter by as apply air fan. The cooled air is then supplied to different zones as shown in the figure. In this HVAC system, the supply air pressure is regulated by the speed of a supply air fan. Increasing the fan speed will increase the supply air pressure, and vice versa. The dynamics of the control signal feeding to the fan Variable Speed Drive to the supply air pressure can be modeledasa second order plus dead time plant. A. Performance Analysis of the STFPIC Study as well as analysis is made if the performance of STFPIC is applied under normal condition and changing of HVAC process model. Under Normal Condition: The transfer function of the supply Air pressure loop under normal condition is obtained as G(s) =0.81e−2s/(0.97s+1)(0.1s+1) Where gain(K)=0.81,τ1=0.97,τ2 =0.1anddeadtime(δ) =2sec. For this process scaling factors are set at Ne =0.9,NΔe=5andNu =2.5. Under HVAC Process Parameters Variation:
1) When gain(K)=0.81,τ1=0.2,τ2=2anddeadtime(δ)=2sec.,thenthetransferfunctionofthesupplyairpressureloopisobtainedas
G(s) =0.81e−2s/(0.2s+1)(2s+1). For this process scaling factors are set at Ne =0.9,NΔe=15andNu =0.3. 2) When gain(K)=1.2,τ1=0.97,τ2 =0.1anddeadtime (δ)=3sec.,thenthetransfer function of the supply air pressure loop is obtained as G(s) =1.2e−3s/ (0.97s+1) (0.1s+1). For this process scaling factors are set at Ne=0.9,NΔe=3 and Nu=1. 3) When gain(K)=1.2,τ1=0.97,τ2 =0.1anddeadtime (δ)=4sec.,thenthetransfer function of the supply air pressure loop is obtained as G(s) =1.2e−4s/ (0.97s+1)(0.1s+1). For this process scaling factors are set at Ne =0.9,NΔe=3andNu =1. TheFig.4, Fig.5, Fig.6, Fig.7 and Table3 are shown that the supply air pressure loop of HVAC works satisfactorily both under normal and as well as under model variations. Table3 refers that both the rise time and settling time is very much satisfactory. Peak over shoots are also shown negligible when STFPIC is used.
5. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 28|
B. Comparison of Practical Performance with Existing Methods. In order to demonstrate the effectiveness and robustness, the performance of the proposed STFPI Chas been compared with those of existing methods, the Bi, Cai’s PID controller and Jian, Cai’s ANF controller[22] for supply air pressure loop control. The comparison has been done under changing process model. The results are provided in Table4. For the application of STFPIC, substantial improvements have been observed in settling time and also in peak over shoot for all the transfer function of the air supply model compare to ANF and PID controller. Furthermore, it is more important that when the process encounters large parameter variations, the method providedpresentsmuchrobustnessasshowninTable4.
6. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 29|
IV. Application of Fuzzy Control for Optimal Operation of Complex Chilling Systems 4.1 Requirements for the design of the fuzzy control system The fuzzy control system is needed to ensure supply of the required cooling power during the operating time of the building by the lowest cost and the shortest system operating time with a low range of set point error for the supply temperature. The concept of knowledge engineering by measurement and analysis of system behavior is necessary, since no expert knowledge has existed for the formulation of the fuzzy rules. Measurement of two physical values of the system is necessary, in order to consider system behavior. These process values are: the outdoor air temperature Tout, which partially presents the thermal behavior of the building, and the user net return temperature (Tr-un), which contains the total cooling load alternation of the building. These requirements focus on three different fuzzy controllers for the different components of the chilling system. The design data for fuzzy controllers has been organized in various tables for the assistance of membership function values of various input variables to a mamdani type fuzzy inference system (FIS).
7. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 30|
Table 5: FUZZY CONTROLLER’S TEMPERATURE DISTRIBUTION DESIGN DATA. SUPPLY TEMPERATURE (HE1) oC SUPPLY TEMPERATURE (HE2) oC EXTERNAL TEMPERATURE Tout (K) oC 4.2 31.1 29.7 5.8 31.2 30.1 6.3 31.5 33 6.9 31.9 34 7.3 33.2 35 8.2 33.4 37 13 33.5 39 14 34.5 42 15 35.4 54
Here, HE2 and HE1 are the respective heat exchangers for evaporator and condenser and Tout is the outdoor air temperature. The fuzzy controller’s set point error difference design data is as shown in table 4.3.Hereerror (e1) and error (e2) gives the difference between the SP (set point value) &MV (measured value) for condenser and evaporator. Tr-un gives the user net return temperature due to individual zone and internal load (occupants, equipment, computers etc). Tr-un gives the difference between user net return temperature and set point temperature. Tout gives the difference between user net return temperature and outdoor air temperature and d Tout/ dt gives the difference between outdoor air temperature by cycle and -cycle. The assessment of refrigeration is made from the coefficient of performance (COP).It depends upon evaporator temperature Te and condensing temperature Tc.
COP Carnot= COP in industry calculated for type of compressor:
COP= 4.2Thermal analysis of the building and chilling system The aim of the thermal analysis of the building is to find measure able information for the needed current cooling load. Alternation for internal cooling load of computers and machines could not be exactly registered or measured. It has been proven by measurement of current cooling power of the building as shown in fig.2thatthereisnota significant correlation between T out and the current cooling power. Also, at higher internal load, there is a heat transmission to the outdoor air space, if Tout is lower than33°C.The current cooling power will increase, if Tout gets higher than 33°C. Al though the equipment and computers are on service for 24 hours a day, there is a big alternation of cooling power. In the summertime, when the Tout increasestoabout45°C,the current cooling power will be more influenced by Tout. So Tout can be used for fore casting the maximum cooling power. Additional information is necessary, in order to analyze the thermal behavior of the building. This information is gained by measuring the user net return temperature(Tr-un). Any change of total cooling load will influence Tr-un and is an important input for the fuzzy controller.
Fig.9: Alternation of current cooling power and outdoor air temperature.
8. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 31|
4.3 Description of the Chilling System The chilling system described here supplies chill water to the air conditioning systems (AC-systems) installed in basement at Ansal Highway Plaza, Jalandhar (Punjab), Indiaasshowninfig.1.There search conditions are ensured by the AC systems by supplying conditioned air to the building. The amount of cooling power for the building is the sum of internal cooling load (produced by occupants, equipment and computers) and the external cooling load, which depends on outdoor air temperature (Tout) and sun radiation through the windows. The compression cooling method is made use of by the cooling machines installed here. The principle of a compression cooling machine can be described in two thermodynamically processes. In the first step of the cooling process, the heat energy will be transferred from the system to the heat exchanger (evaporator) of the cooling machine, and therefore the liquid gas will evaporate by absorbing the heating energy. After the compression of the heated gas, in the second part of the process, the gas condenses again by cooling the gas through the air cooling system. In that step of the process, the heat transfer is from the condensation system to the outdoor air space. The process is continuous, and based on the second law of the thermodynamics. The vap our compression chiller system consists of following components. (a)Compressor: It acts as are claiming agent. (b)Condenser and Evaporator: These acts as a heat exchangers. (c)Expansion Device: It acts as a throttling device to expand the liquid refrigerant. (d)Refrigerant: It acts as a working fluid which absorbs heat from the fluid to be cooled and rejects heat to the atmosphere, through evaporation and condensation. The schematicofavapour compression chiller system is as showninfig.10.
Fig.10: Schematic of a water-cooled chiller system. During the operation of the cooling machines, the air cooling systems will be used and the condensation energy of the cooling machine is transferred to the outdoor air space. If the outdoor air temperature is much lower than user net return temperature on heat exchanger one, the air cooling system should serve as a free cooling system and replace the cooling machine. 4.4 Fuzzy controller1 for operation of the cooling load storage system. The optimum start point for the discharge of the cooling load storage system depends on the maximum cooling power needed, which can differ every day. For calculation of maximum cooling power, Tout must be processed by the fuzzy controller, since the maximum cooling power in the summer time will be influenced extremely by Tout. A feed back of current cooling power calculated by Fuzzy control Block2 is also necessary, in order to estimate the maximum cooling power. If the peak of a maximum cooling power is estimated by the fuzzy controller, then this will be compensated by optimally discharging the cooling load storage system parallel to the cooling machines.
9. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 32|
Fig.11:Fuzzycontroller1foroptimallydischargingcooling load storage system. Theinputvariablesofthecontroller1are: (1)Outdoor air temperature Tout (2)Differential of T out (3) Current cooling power of the cooling machines. For the fuzzification of the Tout, we have following system knowledge. Observation of the system has shown that above Toutof45°C, a second cooling machine is necessary, in order to meet demand for increasing cooling load. There fore the fuzzification will be around Tout45° C with only three fuzzy sets. The second fuzzy variable is calculated by eqn(4.1) D Tout/dt=(Tout(k)-Tout(k-1)) (4.1) With Tout(k)=outdoor air temperature by Kth cycle
Tout( k-1)=outdoor air temperature by–1TH cycle.
The third input variable is the output K value1THofthe Fuzzy controller2, and represents the current cooling power. The output of the fuzzy controller1 is the estimated maximum cooling power CP-max. The membership function used for the fuzzy variables are available as P, Z, trapmf, trimf andS- functions. For the defuzzification,"Centre of maximum "has been supported by the Mamdani type FIS (Fuzzy Inference System) Fig.4shows the P membership function as calculated byequation4.2 X=MAX{0, MIN[1,B/(B-C) – AB(1/(B-C) (K-A))]} (4.2)
Witho=degree of membership X=process variable as input variable
A,B and C=parameters for the membership functions in value of the input variable, e.g. Membership function P type : Therule viewerforfuzzycontroller1isasshowninFig.12
10. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 33|
Fig.12: Rule viewer for fuzzy controller 4.5Fuzzycontroller2 for the operation of the cooling machines The fuzzy controller 2(FC-2) is the important part of the optimization control system, so that the cooling potential of the outdoor air is used, before starting any cooling machine. If"e1" is zero, or negative, then the capacity of free cooling system is enough for the required cooling power. The output signal of FC- 2willbezero.Inothercases,FC-2isresponsible for the operationofthecoolingmachines.Thiscontrollerconsistsof3 input variables as following: (1)Setpointerror"e1"atheatexchanger1 (2)Setpointerror"e2"atheatexchanger2 (3)Difference between user net return temperature (Tr-un) and T set point. The input variable1, is calculated as the difference between user net set point temperature (Tset point), and output temperature of the heat exchanger (THE1) according toequation4.3. e1=Tset point–THE1 (4.3) For this variable, only three sets are necessary, in order to defineif,e1is NS,ZRorPS.Therangeofe1isbetween+1k and- 1k.Thesecondinputvariable is calculated as the difference between(T set point), and output temperature of heatexchanger2(THE2) according toequation4.4 e2=Tset point-THE2 (4.4) The third input variable is determined by equation 3.5 Tr-un=Tr-un-Tset point (4.5) Calculation of Tr-un is necessary, because Tset point is variable, and therefore Tr-un contains the real information about the cooling load of the building.
As soon as the first variable of the controller "e1" reaches the values of PS or ZR, this indicates that the capacity of FC-system is enough to cover the demanded cooling power, and the output signal for cooling machines is zero. In cases, where the capacity of the free cooling system is not enough, "e" will have values of NS, so that output of the controller will be determined by other rules. In that case the third input variable Tr-un is more weighted for the output value of the controller, because Tr- un represents the real alternation of the cooling load of the building. As shown in fig.5, the mamdani type fuzzy inference system (FIS) consists of calculation of input variables such as supply temperature HE1 set point error e1,supply temperature HE2 set point error e2 and user net return temperature Tr- un, then through the process of fuzzification, fuzzy inference
11. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 34|
and defuzzification. The processing of output for current cooling power (CCP) takes place takes place in mamdani type fuzzy inference system (FIS).
Fig.13: Fuzzy controller2 for optimal operation of cooling machines.
Fig.14: Rule view er for fuzzy controller. V. Conclusion From the above elucidation, the process of controlling using fuzzy PI Controller can be clearly understood, as the basic process of fuzzy controlby using variables which come across in HVAC System operation is meticulously depicted. The different types of fuzzies and its operations are explained in the above paragraphs with its applications. These applications are very helpful to know the importance of fuzzy. The variations of the controlling processes are explained with the help of graphs.
12. Heat Ventilation & Air- Conditioning System with Self-Tuning Fuzzy PI Controller
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss.9| Sept. 2014 | 35|
REFERENCES
[1] T. Takagi and M. Sugeno, “Fuzzy identification of systems and its applications to modeling and control,” IEEE Trans. Syst., Man, Cybern. vol. 15, 1985. [2] W. Pedrycz, “An identification algorithm in fuzzy relational systems,” Fuzzy Sets Syst., vol. 13, pp. 153 – 167, 1984. [3] W. Pedrycz and J. V. de Oliveira, “Optimization of fuzzy models,” IEEE Trans. Syst., Man, Cyber., vol. 26, no.4, Feb.1996. [4] R. Alcala, J. Casillas, O. Cordon, A. Gonzalez, and F. Herrera, “A genetic rule weighting and selection process for fuzzy control of heating, ventilation and air conditioning systems,” Engineering application of Artificial Intelligence 28 (2005) 279 – 296. [5] Qiang Xiong, Wen-Jian Cai and Ming He, “A practical decentralized PID auto-tuning method for TITO systems under closed –loop control,” International Journal of Innovative Computing, Information and Control, vol.2, No.2, April.2006. [6] Qing-Gao Wang, Chang-Chieh Hang, Yong Zhang and Qiang Bi,“Multivariable Controller Auto-Tuning with its Application in HVAC Systems,” Proceedings of the American Control Conference, California, June.1999. [7] R.K.Mudi and N.R.Pal, “A robust self-tuning scheme for PI and PDtype fuzzy controllers,” IEEE trans. on fuzzy sys. vol. 7, no. 1, Feb.1997. [18] Qiang Bi, Wenjian Cai and et al, “Advanced controller auto-tuning and its application in HVAC systems,” Control Engineering Practice, 2000. [8] D. Dirankov, H. Hellendorn and M. Reintrank, “An introduction to Fuzzy Control,” New York: Spinger-Verlag, 1993. [9] K. Ogata, “Modern Control Engineering,” Englewood Cliffs, NJ: Prentice-Hall, 1970. [10] W. Jian and C. Wenjian, “Development of an adaptive neuro-fuzzy method for supply air pressure control in HVAC system,” Syst., Man, Cybern., IEEE, 2000. [11] Z. R. Radakovic, V. M. Milosevic, S. B. Radakovic, “Application of temperature fuzzy controller in an indirect resistance furnace,” Applied Energy. 73 (2002) 167-182. [12] H.R.Benerji, Fuzzy Logic Controllers, in: R. R. Yager, L. A. Zadeh (Eds.), “An introduction to Fuzzy logic application in intelligent systems,00 Kluwer, Boston, MA, 1992. [13] H. J. Zimmermann, “Fuzzy sets theory and its applications.” Kluwer, Nijhoa, Boston, Dordrecht, Lancaster, 1984. Singapore: World Scientific,1993. [14] Kim J-H, Kim K-C, Chong EKP, “Fuzzy pre compensated PID controllers,” IEEE Trans. Con. Syst. Technology, 1994: 2(4). [15] Cho Hyun-Joon, Cho Kwang-Bo, Wang Bo- Hyeun, “Fuzzy-PID hybrid control: automatic rule generation using genetic algorithm,” Fuzzy sets and systems, 1997, 92(3), 305-316. [16] Wu Zhi Qiao, Masaharu Mizumoto, Fuzzy sets and systems 78 (1996), 23-35. [17] M. Sugeno, “Industrial applications of Fuzzy Control,”Amsterdam, Netherlands: Elsevier,1985. [18] M. Sugeno and K. Tanaka, “Successive identification of a fuzzy model and its application to predi- ction of a complex system,” Fuzzy Sets Syst., vol. 42, pp. 315 – 334, 1991. [19] M. Sugeno and T. Yasukawa, “ A fuzzy–logic- based approach to qualitative modeling,” IEEE Trans. Fuzzy Syst., vol. 1, pp. 7 – 31, Feb.1993. [20] R. M. Tong, “The construction and evaluation of fuzzy models,” in advances in Fuzzy Set Theory and applications ed. M. M. Gupta et. al., North Holland, 1979. [21] R. Palm, “Sliding mode fuzzy control”, in Proc. Fuzz IEEE, San Diego, CA, 1992, pp. 519-526.