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.
Design and Control of a Hydraulic Servo System and Simulation AnalysisIJMREMJournal
This paper describes the system analysis, modeling and simulation of a Hydraulic Servo System (HSS) for
hydraulic mini press machine. Comparisons among linear output feed back PID control, Fuzzy control and
Hybrid of PID and Fuzzy control are presented. Application of hybrid controller to a nonlinear is investigated
by both position and velocity of the hydraulic servo system. The experiment is based on an 8 bit PIC
16F877 microcontroller, and the simulation is based on MATLAB Simulink. Simulation and hardware
experimental results show that the hybrid controller gave the best performance as it has the smallest overshoot,
oscillation, and setting time.
This document compares the performance of indirect vector control of an induction motor using proportional-integral (PI) and proportional-integral-derivative (PID) speed controllers. It first provides background on induction motors, vector control techniques, and PI/PID controllers. It then presents the simulation model and results, which show the PID controller provides better speed response characteristics like shorter settling time. In conclusion, the PID controller improves the speed performance for indirect vector control of an induction motor drive.
Performance Analysis of Direct Torque Controlled BLDC motor using Fuzzy LogicIAES-IJPEDS
The Brushless DC motor (BLDC) control is used in many of the applications
as it is small in size and with low power which can drive in high speed and
lighter compared to other motors.The electric vehicles are built with BLDC
motors and also in ships, aerospace etc., The control of BLDC motors is done
with sensors like hall effect sensor for sensing the positions. The speed
control can be done with normal PI and PID controllers. Direct torque control
(DTC) of the BLDC motor is important in many applications. In this paper
BLDC motor is controlled with DTC using PI, PID and Fuzzy logic control.
The comparison of the performance of the motor is analyzed with the Matlab
simulation software.
Experiment based comparative analysis of stator current controllers using pre...journalBEEI
The stator current control loop plays an important role in ensuring the quality of electric drives interm of producing fast and adequate required torque. When the current controller provides ideal responses, speed control design subsequently is in charge of improving the system performances. Classical PID control is commonly used in current loop design, this paper presents the comparative analysis of current stator controller using proportional integral control and predictive current control (PCC) in field-oriented control-based induction motor drives, with rigidly coupled loads. The experimental results show system responses with PID and PCC. Informative experiment-based analysis provides primary guidance in selection between the two controls.
Internal Model Based Vector Control of Induction MotorIJMER
This paper deals with the design of PID and Internal Model Controllers (IMC) in adjusting
the speed of induction machine under disturbances and set point changes. The performance of PID
controller is compared with IMC. The internal model control is an alternative to the classic feedback
structure. Internal model control is composed of an inverse model connected in series with the plant and a
forward model connected in parallel with the plant, this structure allows the error feedback to reflect the
effect of disturbances and plant mismodelling resulting in a robust control loop. The IMC provides good
performance and robustness against the disturbances in system when compared with the PID controller. A
simulation study of these methods is presented using MATLAB/SIMULINK.
Pid parameters optimization using adaptive pso algorithm for a dcsm positiIAEME Publication
The document summarizes research on optimizing the parameters of a PID controller to control the position of a DC servomotor. It compares four tuning methods: Ziegler-Nichols, standard particle swarm optimization (SPSO), modified particle swarm optimization (MPSO), and adaptive particle swarm optimization (APSO). The results showed that the proposed APSO algorithm gives better performance than the other optimization algorithms in terms of achieving faster response of the DC servomotor to reach the final position.
This document proposes a fuzzy logic and neural network-based method for identifying the temperature condition of aircraft gas turbine engines. At early stages of operation when data is limited and uncertain, fuzzy logic and neural networks can be used to create an initial model of the engine's condition. As more normal distribution data is collected over 60-120 measurements, mathematical statistics methods are applied, including analyzing parameters within calculated fuzzy admissible and possible ranges. The method also identifies linear regression models for the engine's initial and actual conditions and compares them to monitor changes using fuzzy correlation and regression analysis. This combined fuzzy-statistical approach allows improved gas turbine engine condition monitoring and diagnostics.
PID controller for microsatellite yaw-axis attitude control system using ITAE...TELKOMNIKA JOURNAL
The need for effective design of satellite attitude control (SAC) subsystem for a microsatellite is imperative in order to guarantee both the quality and reliability of the data acquisition. A proportional-integral-derivative (PID) controller was proposed in this study because of its numerous advantages. The performance of PID controller can be greatly improved by adopting an integral time absolute error (ITAE) robust controller design approach. Since the system to be controlled is of the 4th order, it was approximated by its 2nd order version and then used for the controller design. Both the reduced and higher-order pre-filter transfer functions were designed and tested, in order to improve the system performance. As revealed by the results, three out of the four designed systems satisfy the design specifications; and the PD-controlled system without pre-filter transfer function was recommended out of the three systems due to its structural simplicity, which eventually enhances its digital implementation.
Design and Control of a Hydraulic Servo System and Simulation AnalysisIJMREMJournal
This paper describes the system analysis, modeling and simulation of a Hydraulic Servo System (HSS) for
hydraulic mini press machine. Comparisons among linear output feed back PID control, Fuzzy control and
Hybrid of PID and Fuzzy control are presented. Application of hybrid controller to a nonlinear is investigated
by both position and velocity of the hydraulic servo system. The experiment is based on an 8 bit PIC
16F877 microcontroller, and the simulation is based on MATLAB Simulink. Simulation and hardware
experimental results show that the hybrid controller gave the best performance as it has the smallest overshoot,
oscillation, and setting time.
This document compares the performance of indirect vector control of an induction motor using proportional-integral (PI) and proportional-integral-derivative (PID) speed controllers. It first provides background on induction motors, vector control techniques, and PI/PID controllers. It then presents the simulation model and results, which show the PID controller provides better speed response characteristics like shorter settling time. In conclusion, the PID controller improves the speed performance for indirect vector control of an induction motor drive.
Performance Analysis of Direct Torque Controlled BLDC motor using Fuzzy LogicIAES-IJPEDS
The Brushless DC motor (BLDC) control is used in many of the applications
as it is small in size and with low power which can drive in high speed and
lighter compared to other motors.The electric vehicles are built with BLDC
motors and also in ships, aerospace etc., The control of BLDC motors is done
with sensors like hall effect sensor for sensing the positions. The speed
control can be done with normal PI and PID controllers. Direct torque control
(DTC) of the BLDC motor is important in many applications. In this paper
BLDC motor is controlled with DTC using PI, PID and Fuzzy logic control.
The comparison of the performance of the motor is analyzed with the Matlab
simulation software.
Experiment based comparative analysis of stator current controllers using pre...journalBEEI
The stator current control loop plays an important role in ensuring the quality of electric drives interm of producing fast and adequate required torque. When the current controller provides ideal responses, speed control design subsequently is in charge of improving the system performances. Classical PID control is commonly used in current loop design, this paper presents the comparative analysis of current stator controller using proportional integral control and predictive current control (PCC) in field-oriented control-based induction motor drives, with rigidly coupled loads. The experimental results show system responses with PID and PCC. Informative experiment-based analysis provides primary guidance in selection between the two controls.
Internal Model Based Vector Control of Induction MotorIJMER
This paper deals with the design of PID and Internal Model Controllers (IMC) in adjusting
the speed of induction machine under disturbances and set point changes. The performance of PID
controller is compared with IMC. The internal model control is an alternative to the classic feedback
structure. Internal model control is composed of an inverse model connected in series with the plant and a
forward model connected in parallel with the plant, this structure allows the error feedback to reflect the
effect of disturbances and plant mismodelling resulting in a robust control loop. The IMC provides good
performance and robustness against the disturbances in system when compared with the PID controller. A
simulation study of these methods is presented using MATLAB/SIMULINK.
Pid parameters optimization using adaptive pso algorithm for a dcsm positiIAEME Publication
The document summarizes research on optimizing the parameters of a PID controller to control the position of a DC servomotor. It compares four tuning methods: Ziegler-Nichols, standard particle swarm optimization (SPSO), modified particle swarm optimization (MPSO), and adaptive particle swarm optimization (APSO). The results showed that the proposed APSO algorithm gives better performance than the other optimization algorithms in terms of achieving faster response of the DC servomotor to reach the final position.
This document proposes a fuzzy logic and neural network-based method for identifying the temperature condition of aircraft gas turbine engines. At early stages of operation when data is limited and uncertain, fuzzy logic and neural networks can be used to create an initial model of the engine's condition. As more normal distribution data is collected over 60-120 measurements, mathematical statistics methods are applied, including analyzing parameters within calculated fuzzy admissible and possible ranges. The method also identifies linear regression models for the engine's initial and actual conditions and compares them to monitor changes using fuzzy correlation and regression analysis. This combined fuzzy-statistical approach allows improved gas turbine engine condition monitoring and diagnostics.
PID controller for microsatellite yaw-axis attitude control system using ITAE...TELKOMNIKA JOURNAL
The need for effective design of satellite attitude control (SAC) subsystem for a microsatellite is imperative in order to guarantee both the quality and reliability of the data acquisition. A proportional-integral-derivative (PID) controller was proposed in this study because of its numerous advantages. The performance of PID controller can be greatly improved by adopting an integral time absolute error (ITAE) robust controller design approach. Since the system to be controlled is of the 4th order, it was approximated by its 2nd order version and then used for the controller design. Both the reduced and higher-order pre-filter transfer functions were designed and tested, in order to improve the system performance. As revealed by the results, three out of the four designed systems satisfy the design specifications; and the PD-controlled system without pre-filter transfer function was recommended out of the three systems due to its structural simplicity, which eventually enhances its digital implementation.
This document describes a new design method for fractional-order PID (FOPID) controllers. It introduces a biquadratic approximation of fractional-order differential operators to create a new structure for finite-order FOPID controllers with fewer parameters to tune than existing designs. The proposed FOPID controller design uses the biquadratic approximation within a modular design approach, cascading multiple modules to improve robustness. A numerical example is used to verify the design method.
Hexacopter using MATLAB Simulink and MPU SensingIRJET Journal
This document describes the modeling and control of a hexacopter unmanned aerial vehicle using MATLAB simulation. It presents the mathematical modeling of the hexacopter dynamics using Newton-Euler angles and reference frames. PID controllers are developed for altitude, roll, pitch and yaw control. The rotor speeds required for thrust and attitude control are calculated from the PID outputs. Simulation parameters are provided and the results obtained from implementing the PID controllers on the hexacopter model in MATLAB are presented.
This document presents a new control structure using a PID controller for load frequency control of power systems. The control structure places the PID controller in the feedback loop to improve disturbance rejection and robustness against plant parameter uncertainties. A relay feedback method is used to identify lower order transfer function models with time delay from typically higher order power system models. The PID controller parameters are then tuned using Laurent series expansion of the closed loop transfer function to provide improved performance for disturbance rejection while maintaining robustness. Simulation results on single-area and multi-area power system models demonstrate the effectiveness of the proposed control structure and PID controller design method.
This document describes a model-based autotuning system that uses an artificial neural network (ANN) and relay feedback test. The system estimates process parameters like gain, ultimate gain, ultimate frequency, and apparent deadtime from relay feedback test data. It then classifies the process dynamics and tunes PI/PID controllers based on either a first-order plus deadtime or second-order plus deadtime process model. The tuning rules are derived from these models to provide superior control performance compared to Ziegler-Nichols tuning.
IRJET- Analysis of 3-Phase Induction Motor with High Step-Up PWM DC-DC Conver...IRJET Journal
This document discusses control methods for STATCOMs using fuzzy logic controllers and genetic algorithm-tuned PID controllers. STATCOMs are shunt FACTS devices that help solve power quality issues through fast reactive power control. Conventionally, PID controllers are used but require trial and error to tune parameters. The document proposes using fuzzy logic controllers and genetic algorithms to optimize PID parameters to improve STATCOM current control response. It describes STATCOM modeling, fuzzy logic controller design including fuzzification, inference, and defuzzification. Genetic algorithms are used to find optimal PID parameters. Simulation results in MATLAB show the proposed methods improve current control response over conventional PID control.
Design of Fractional Order PID controller using Soft computing methods for a ...IOSR Journals
This document describes a study that designs a fractional order PID (FOPID) controller using soft computing methods for a buck-boost DC-DC power converter. A FOPID controller is proposed to improve the dynamic response of the converter compared to a conventional PID controller. Particle swarm optimization and cuckoo search algorithms are used to tune the parameters of the FOPID controller (KP, Ki, Kd, λ, μ) to regulate the output voltage. Simulation results show that the FOPID controller designed with both algorithms achieves faster response times, lower overshoot, and better settling performance compared to a PID controller.
Simulation DC Motor Speed Control System by using PID Controllerijtsrd
Speed control system is the most common control algorithm used in industry and has been universally accepted in industrial control. One of the applications used here is to control the speed of the DC motor. Controlling the speed of a DC motor is very important as any small change can lead to instability of the closed loop system. The aim of this thesis is to show how DC motor can be controlled by using PID controller in MATLAB. The development of the PID controller with the mathematical model of DC motor is done using automatic tuning method. The PID parameter is to be test with an actual motor also with the PID controller in MATLAB Simulink. In this paper describe the results to demonstrate the effectiveness and the proposed of this PID controller produce significant improvement control performance and advantages of the control system DC motor. Mrs Khin Ei Ei Khine | Mrs Win Mote Mote Htwe | Mrs Yin Yin Mon ""Simulation DC Motor Speed Control System by using PID Controller"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25114.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/25114/simulation-dc-motor-speed-control-system-by-using-pid-controller/mrs-khin-ei-ei-khine
This document proposes a method for identifying the temperature condition of aircraft gas turbine engines using fuzzy logic and neural networks. It involves a multi-stage process of evaluating engine parameters at different stages of operation. In the early stages when data is limited and uncertain, fuzzy logic and neural networks are used to create an initial model of the engine condition. As more data is obtained, mathematical statistics methods and regression analysis are applied to identify linear regression models of the engine temperature condition. A neural network structure is used to identify the fuzzy regression coefficients in the models based on statistical fuzzy data from experiments. This allows monitoring of the engine condition at different operational stages in a way that accounts for uncertainty and limitations in the early data.
Performance Analysis of a DTC and SVM Based Field- Orientation Control Induct...IJPEDS-IAES
This study presents a performance analysis of two most popular control strategies for Induction Motor (IM) drives: direct torque control (DTC) and space vector modulation (SVM) strategies. The performance analysis is done by applying field-orientation control (FOC) technique because of its good dynamic response. The theoretical principle, simulation results are discussed to study the dynamic performances of the drive system for individual control strategies using actual parameters of induction motor. A closed loop PI controller scheme has been used. The main purpose of this study is to minimize ripple in torque response curve and to achieve quick speed response as well as to investigate the condition for optimum performance of induction motor drive. Depending on the simulation results this study also presents a detailed comparison between direct torque control and space vector modulation based field-orientation control method for the induction motor drive.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
The document discusses fractional order PID tuning and control. It introduces fractional order systems and controllers (FOPID), and describes some of their advantages over traditional PID controllers, including better modeling of dynamic systems and more robust control design. It then discusses several FOPID tuning methods, focusing on the Taylor series expansion method which matches terms between the actual and desired closed-loop transfer functions to increase tracking accuracy.
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.
Automatic control and mixed sensitivity Hinf controlRené Galindo
This document provides an overview of automatic control and mixed sensitivity H∞ control. It begins with background on automatic control, including its history, basic notions such as feedback and components, and types of controllers and control objectives. It then discusses mixed sensitivity H∞ control, including the motivation of robustness to uncertainty, basic notions such as the infinity norm and robust H∞ control objective. It also covers uncertainty models and loop shaping techniques. The document provides context and definitions regarding automatic control and mixed sensitivity H∞ control.
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.
Speed Control of Induction Motor by Using Intelligence TechniquesIJERA Editor
This paper gives the comparative study among various techniques used to control the speed of three phase induction motor. In this paper, indirect vector method is used to control the speed of Induction motor. Firstly Simulink Model is developed by using MATLAB/ Simulink software. PI controller, Fuzzy PI Hybrid controller, Genetic Algorithm (GA) are the techniques involved in control Induction motor and the results are compared. By converting three phase supply currents coming from stator to Flux and Torque components of current the speed responses such as rise time, overshoot, settling time and speed regulation at load have been observed and compared among the techniques. The PI controller parameters defined by an objective function are calculated by using Genetic Algorithms presented good performance compared to Fuzzy PI Hybrid controller which has parameters chosen by the human operator.
Antenna Azimuth Position Control System using PIDController & State-Feedback ...IJECEIAES
This paper analyzed two controllers with the view to improve the overall control of an antenna azimuth position. Frequency ranges were utilized for the PID controller in the system; while Ziegler-Nichols was used to tune the PID parameter gains. A state feedback controller was formulated from the state-space equation and pole-placements were adopted to ensure the model design complied with the specifications to meet transient response. MATLAB Simulink platform was used for the system simulation. The system response for both the two controllers were analyzed and compared to ascertain the best controller with best azimuth positioning for the antenna. It was observed that state-feedback controller provided the best azimuth positioning control with a little settling time, some value of overshoot and no steady-state error is detected.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
A comparative study of controllers for stabilizing a rotary inverted pendulumijccmsjournal
The document describes a comparative study of various controllers - PID, LQR, fuzzy logic, and H-infinity - for stabilizing a rotary inverted pendulum (RIP) system. The controllers are modeled and tested in MATLAB Simulink. Key findings:
- PID control stabilizes the pendulum angle to zero within 1 second.
- LQR control stabilizes the pendulum angle to zero within 1.5 seconds.
- Fuzzy logic control stabilizes the pendulum angle within 0.5 seconds.
- H-infinity control provides robust stabilization of the RIP system.
6. performance analysis of pd, pid controllers for speed control of dc motork srikanth
Aim of this paper different Proportional-Integral- Derivative (PID) controller fine-tuning techniques are investigated for speed control of DC motor. At the start PID controller parameters for different tuning techniques are involved and then applied to the DC motor model for motion (speed) control. Simulation results are display, using these controllers, objective of this paper, the performance of a choose dc motor controlled by a proportional-integral-derivative (PID) controller is below the similar transient conditions and performances are compared.
IRJET- Design and Analysis of Fuzzy and GA-PID Controllers for Optimized Perf...IRJET Journal
This document describes research into using different controller types, including fuzzy logic controllers and genetic algorithm optimized PID controllers, to control a STATCOM device for improved reactive power compensation performance. A STATCOM is a shunt Flexible AC Transmission System device that can help solve power quality issues. Conventionally, PID controllers are used but require trial and error to tune parameters. The document models a STATCOM system and explores using fuzzy logic control or genetic algorithms to automatically determine optimal PID parameters to achieve faster response compared to conventional PID control. Simulation results in MATLAB show that both fuzzy logic control and genetic algorithm optimized PID control improve the STATCOM current control response compared to manually tuned PID controllers.
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.
This document describes a new design method for fractional-order PID (FOPID) controllers. It introduces a biquadratic approximation of fractional-order differential operators to create a new structure for finite-order FOPID controllers with fewer parameters to tune than existing designs. The proposed FOPID controller design uses the biquadratic approximation within a modular design approach, cascading multiple modules to improve robustness. A numerical example is used to verify the design method.
Hexacopter using MATLAB Simulink and MPU SensingIRJET Journal
This document describes the modeling and control of a hexacopter unmanned aerial vehicle using MATLAB simulation. It presents the mathematical modeling of the hexacopter dynamics using Newton-Euler angles and reference frames. PID controllers are developed for altitude, roll, pitch and yaw control. The rotor speeds required for thrust and attitude control are calculated from the PID outputs. Simulation parameters are provided and the results obtained from implementing the PID controllers on the hexacopter model in MATLAB are presented.
This document presents a new control structure using a PID controller for load frequency control of power systems. The control structure places the PID controller in the feedback loop to improve disturbance rejection and robustness against plant parameter uncertainties. A relay feedback method is used to identify lower order transfer function models with time delay from typically higher order power system models. The PID controller parameters are then tuned using Laurent series expansion of the closed loop transfer function to provide improved performance for disturbance rejection while maintaining robustness. Simulation results on single-area and multi-area power system models demonstrate the effectiveness of the proposed control structure and PID controller design method.
This document describes a model-based autotuning system that uses an artificial neural network (ANN) and relay feedback test. The system estimates process parameters like gain, ultimate gain, ultimate frequency, and apparent deadtime from relay feedback test data. It then classifies the process dynamics and tunes PI/PID controllers based on either a first-order plus deadtime or second-order plus deadtime process model. The tuning rules are derived from these models to provide superior control performance compared to Ziegler-Nichols tuning.
IRJET- Analysis of 3-Phase Induction Motor with High Step-Up PWM DC-DC Conver...IRJET Journal
This document discusses control methods for STATCOMs using fuzzy logic controllers and genetic algorithm-tuned PID controllers. STATCOMs are shunt FACTS devices that help solve power quality issues through fast reactive power control. Conventionally, PID controllers are used but require trial and error to tune parameters. The document proposes using fuzzy logic controllers and genetic algorithms to optimize PID parameters to improve STATCOM current control response. It describes STATCOM modeling, fuzzy logic controller design including fuzzification, inference, and defuzzification. Genetic algorithms are used to find optimal PID parameters. Simulation results in MATLAB show the proposed methods improve current control response over conventional PID control.
Design of Fractional Order PID controller using Soft computing methods for a ...IOSR Journals
This document describes a study that designs a fractional order PID (FOPID) controller using soft computing methods for a buck-boost DC-DC power converter. A FOPID controller is proposed to improve the dynamic response of the converter compared to a conventional PID controller. Particle swarm optimization and cuckoo search algorithms are used to tune the parameters of the FOPID controller (KP, Ki, Kd, λ, μ) to regulate the output voltage. Simulation results show that the FOPID controller designed with both algorithms achieves faster response times, lower overshoot, and better settling performance compared to a PID controller.
Simulation DC Motor Speed Control System by using PID Controllerijtsrd
Speed control system is the most common control algorithm used in industry and has been universally accepted in industrial control. One of the applications used here is to control the speed of the DC motor. Controlling the speed of a DC motor is very important as any small change can lead to instability of the closed loop system. The aim of this thesis is to show how DC motor can be controlled by using PID controller in MATLAB. The development of the PID controller with the mathematical model of DC motor is done using automatic tuning method. The PID parameter is to be test with an actual motor also with the PID controller in MATLAB Simulink. In this paper describe the results to demonstrate the effectiveness and the proposed of this PID controller produce significant improvement control performance and advantages of the control system DC motor. Mrs Khin Ei Ei Khine | Mrs Win Mote Mote Htwe | Mrs Yin Yin Mon ""Simulation DC Motor Speed Control System by using PID Controller"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25114.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/25114/simulation-dc-motor-speed-control-system-by-using-pid-controller/mrs-khin-ei-ei-khine
This document proposes a method for identifying the temperature condition of aircraft gas turbine engines using fuzzy logic and neural networks. It involves a multi-stage process of evaluating engine parameters at different stages of operation. In the early stages when data is limited and uncertain, fuzzy logic and neural networks are used to create an initial model of the engine condition. As more data is obtained, mathematical statistics methods and regression analysis are applied to identify linear regression models of the engine temperature condition. A neural network structure is used to identify the fuzzy regression coefficients in the models based on statistical fuzzy data from experiments. This allows monitoring of the engine condition at different operational stages in a way that accounts for uncertainty and limitations in the early data.
Performance Analysis of a DTC and SVM Based Field- Orientation Control Induct...IJPEDS-IAES
This study presents a performance analysis of two most popular control strategies for Induction Motor (IM) drives: direct torque control (DTC) and space vector modulation (SVM) strategies. The performance analysis is done by applying field-orientation control (FOC) technique because of its good dynamic response. The theoretical principle, simulation results are discussed to study the dynamic performances of the drive system for individual control strategies using actual parameters of induction motor. A closed loop PI controller scheme has been used. The main purpose of this study is to minimize ripple in torque response curve and to achieve quick speed response as well as to investigate the condition for optimum performance of induction motor drive. Depending on the simulation results this study also presents a detailed comparison between direct torque control and space vector modulation based field-orientation control method for the induction motor drive.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
The document discusses fractional order PID tuning and control. It introduces fractional order systems and controllers (FOPID), and describes some of their advantages over traditional PID controllers, including better modeling of dynamic systems and more robust control design. It then discusses several FOPID tuning methods, focusing on the Taylor series expansion method which matches terms between the actual and desired closed-loop transfer functions to increase tracking accuracy.
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.
Automatic control and mixed sensitivity Hinf controlRené Galindo
This document provides an overview of automatic control and mixed sensitivity H∞ control. It begins with background on automatic control, including its history, basic notions such as feedback and components, and types of controllers and control objectives. It then discusses mixed sensitivity H∞ control, including the motivation of robustness to uncertainty, basic notions such as the infinity norm and robust H∞ control objective. It also covers uncertainty models and loop shaping techniques. The document provides context and definitions regarding automatic control and mixed sensitivity H∞ control.
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.
Speed Control of Induction Motor by Using Intelligence TechniquesIJERA Editor
This paper gives the comparative study among various techniques used to control the speed of three phase induction motor. In this paper, indirect vector method is used to control the speed of Induction motor. Firstly Simulink Model is developed by using MATLAB/ Simulink software. PI controller, Fuzzy PI Hybrid controller, Genetic Algorithm (GA) are the techniques involved in control Induction motor and the results are compared. By converting three phase supply currents coming from stator to Flux and Torque components of current the speed responses such as rise time, overshoot, settling time and speed regulation at load have been observed and compared among the techniques. The PI controller parameters defined by an objective function are calculated by using Genetic Algorithms presented good performance compared to Fuzzy PI Hybrid controller which has parameters chosen by the human operator.
Antenna Azimuth Position Control System using PIDController & State-Feedback ...IJECEIAES
This paper analyzed two controllers with the view to improve the overall control of an antenna azimuth position. Frequency ranges were utilized for the PID controller in the system; while Ziegler-Nichols was used to tune the PID parameter gains. A state feedback controller was formulated from the state-space equation and pole-placements were adopted to ensure the model design complied with the specifications to meet transient response. MATLAB Simulink platform was used for the system simulation. The system response for both the two controllers were analyzed and compared to ascertain the best controller with best azimuth positioning for the antenna. It was observed that state-feedback controller provided the best azimuth positioning control with a little settling time, some value of overshoot and no steady-state error is detected.
Fuzzy gain scheduling control apply to an RC Hovercraft IJECEIAES
The Fuzzy Gain Scheduling (FGS) methodology for tuning the ProportionalIntegral-Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional-Integral-Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller.
A comparative study of controllers for stabilizing a rotary inverted pendulumijccmsjournal
The document describes a comparative study of various controllers - PID, LQR, fuzzy logic, and H-infinity - for stabilizing a rotary inverted pendulum (RIP) system. The controllers are modeled and tested in MATLAB Simulink. Key findings:
- PID control stabilizes the pendulum angle to zero within 1 second.
- LQR control stabilizes the pendulum angle to zero within 1.5 seconds.
- Fuzzy logic control stabilizes the pendulum angle within 0.5 seconds.
- H-infinity control provides robust stabilization of the RIP system.
6. performance analysis of pd, pid controllers for speed control of dc motork srikanth
Aim of this paper different Proportional-Integral- Derivative (PID) controller fine-tuning techniques are investigated for speed control of DC motor. At the start PID controller parameters for different tuning techniques are involved and then applied to the DC motor model for motion (speed) control. Simulation results are display, using these controllers, objective of this paper, the performance of a choose dc motor controlled by a proportional-integral-derivative (PID) controller is below the similar transient conditions and performances are compared.
IRJET- Design and Analysis of Fuzzy and GA-PID Controllers for Optimized Perf...IRJET Journal
This document describes research into using different controller types, including fuzzy logic controllers and genetic algorithm optimized PID controllers, to control a STATCOM device for improved reactive power compensation performance. A STATCOM is a shunt Flexible AC Transmission System device that can help solve power quality issues. Conventionally, PID controllers are used but require trial and error to tune parameters. The document models a STATCOM system and explores using fuzzy logic control or genetic algorithms to automatically determine optimal PID parameters to achieve faster response compared to conventional PID control. Simulation results in MATLAB show that both fuzzy logic control and genetic algorithm optimized PID control improve the STATCOM current control response compared to manually tuned PID controllers.
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.
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.
Robust PID Controller Design for Non-Minimum Phase Systems using Magnitude Op...IRJET Journal
This document discusses two approaches for designing a controller for non-minimum phase systems: 1) the magnitude optimum and multiple integration method, and 2) a numerical optimization approach. The magnitude optimum method uses areas calculated from the process step response to determine the PID controller parameters, eliminating the need to estimate process parameters directly. The numerical optimization approach formulates the controller design as an optimization problem to minimize sensitivity functions in the closed-loop system. Both approaches are presented as ways to design robust controllers for non-minimum phase systems.
DC Motor Speed Control for a Plant Based On PID Controllerpaperpublications3
Abstract: This paper aims is to design a controller for controlling the speed of DC motor .The effects of the controller on motor speed is analyzed .Automatic tuning of the controller is also introduce for efficient control of the process .The tuning is implemented using Ziegler Nichols method and results are compared with Variation in speed without controller.
Iaetsd modelling of one link flexible arm manipulator usingIaetsd Iaetsd
This document describes a two-stage controller for controlling an uncertain flexible robotic arm. In the first stage, an outer loop controller is designed to track a desired tip position trajectory, assuming the motor dynamics are negligible. This outer loop controller uses a generalized proportional integral (GPI) design. In the second stage, an inner loop controller is designed to force the motor position to track the trajectory determined by the outer loop controller, despite unknown friction and parameters in the motor dynamics. The two-stage GPI controller provides robust tracking of the tip position trajectory without requiring online estimation of system parameters.
Design of multiloop controller for multivariable system using coefficient 2IAEME Publication
The document describes the design of a multivariable controller for a coupled tank system using the Coefficient Diagram Method (CDM). CDM is a polynomial method for control design that is based on choosing coefficients for the closed-loop system's characteristic polynomial according to desired performance specifications like equivalent time constant, stability indices, and stability limit. The controller is designed by using CDM to determine the coefficients of the controller polynomials. The coupled tank process is modeled using mass balance equations and its parameters are provided. Controller design using CDM is demonstrated for multivariable processes like the coupled tank system to provide stable and robust performance while meeting time domain specifications.
Design of Digital Autopilot for Lateral Motion Control of an Aircraft Based o...IJERA Editor
The optimal digital autopilot needed to control of the roll for an aircraft in the presence of an arbitrary unmeasured disturbances is addressed in this paper. Such autopilot has to achieve a desired lateral motion control of this aircraft via minimizing the upper bound on the absolute value of the difference between the given and true roll angles. It is ensured by means of the two digital controllers. The inner controller is designed as the discrete-time PI controller in order to stabilize a given roll rate. This variable is formed by the external P controller. The necessary and sufficient conditions under which the two-circuit feedback discrete-time control system will be stable are derived. To optimize this control system, the controller parameters are derived utilizing the so-called l1-optimization approach advanced in modern control theory. A numerical example demonstrating the l1-optimization technique and results of some simulation experiments are presented to illustrate the performance of the l1-optimal controller. The robustness properties of this controller are established
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.
Design of Adaptive Sliding Mode Control with Fuzzy Controller and PID Tuning ...IRJET Journal
This document presents a control system that combines fuzzy sliding mode control and PID tuning to control uncertain systems. A fuzzy logic controller is proposed using two inputs (error and derivative of error) and simple membership functions and rules. An adaptive sliding mode controller with PID tuning is also designed. The PID gains are systematically and continuously updated according to adaptive laws. This combined fuzzy sliding mode controller with PID tuning is applied to control a brushless DC motor. Simulation results show the system achieves good trajectory tracking performance while eliminating chattering through the use of a boundary layer.
Non integer order controller based robust performance analysis of a conical t...Editor Jacotech
The design of robust controller for any non linear process is a
challenging task because of the presence of various types of
uncertainties. In this paper, various design methods of robust
PID controller for the level control of conical tank are
discussed. Uncertainties are of different types, among that
structured uncertainty of 30% is introduced to the nominal
plant for analysing the robustness. As a first step, the control
of level is done by using conventional integer order controller
for both nominal and uncertain system. Then, the control is
done by means of Fractional Order Proportional Integral
Derivative (FOPID) controller for achieving robustness. With
the help of time series parameters, a comparison is made
between conventional PID and FOPID with respect to the
simulated output using MATLAB and also analyzed the
robustness.
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.
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
This paper presents an enhanced nonlinear PID (NPID) controller to follow a preselected speed profile of brushless DC motor drive system. This objective should be achieved regardless the parameter variations, and external disturbances. The performance of enhanced NPID controller will be investigated by comparing it with linear PID control and fractional order PID (FOPID) control. These controllers are tested for both speed regulation and speed tracking. The optimal parameters values of each control technique were obtained using Genetic Algorithm (GA) based on a certain cost function. Results shows that the proposed NPID controller has better performance among other techniques (PID and FOPID controller).
This document presents a second order integral sliding mode control approach for speed control of a DC motor system. The DC motor system is modeled as a second order system with uncertainty and disturbances. Three controllers are designed and compared - a second order integral sliding mode controller, a conventional sliding mode controller, and a PID controller. Simulation results show that the proposed second order integral sliding mode controller has the fastest response time, no overshoot, smooth control input, and drives the sliding surface to zero, performing better than the other controllers in terms of robustness and disturbance rejection.
EHR ATTRIBUTE-BASED ACCESS CONTROL (ABAC) FOR FOG COMPUTING ENVIRONMENTcsandit
Liquid level tanks are employed in many industrial and chemical areas. Their level must be keep
a defined point or between maximum-minimum points depending on changing of inlet and outlet
liquid quantities. In order to overcome the problem, many level control methods have been
developed. In the paper, it was aimed that obtain a mathematical model of an installed liquid
level tank system. Then, the mathematical model was derived from the installed system
depending on the sizes of the liquid level tank. According to some proportional-integralderivative
(PID) parameters, the model was simulated by using MATLAB/Simulink program.
After that, data of the liquid level tank were taken into a computer by employing data
acquisition cards (DAQs). Lastly, the computer-controlled liquid level control was successfully
practiced through a written computer program embedded into a PID algorithm used the PID
parameters obtained from the simulations into Advantech VisiDAQ software
A Lyapunov Based Approach to Enchance Wind Turbine Stabilityijeei-iaes
This paper introduces a nonlinear control of a wind turbine based on a Double Feed Induction Generator. The Rotor Side converter is controlled by using field oriented control and Backstepping strategy to enhance the dynamic stability response. The Grid Side converter is controlled by a sliding mode. These methods aim to increase dynamic system stability for variable wind speed. Hence, The Doubly Fed Induction Generator (DFIG) is studied in order to illustrate its behavior in case of severe disturbance, and its dynamic response in grid connected mode for variable speed wind operation. The model is presented and simulated under Matlab/ Simulink.
Abstract - This paper addresses some of the potential benefits of
using fuzzy logic controllers to control an inverted pendulum
system. The stages of the development of a fuzzy logic controller
using a four input Takagi-Sugeno fuzzy model were presented.
The main idea of this paper is to implement and optimize fuzzy
logic control algorithms in order to balance the inverted
pendulum and at the same time reducing the computational time
of the controller. In this work, the inverted pendulum system was
modeled and constructed using Simulink and the performance of
the proposed fuzzy logic controller is compared to the more
commonly used PID controller through simulations using Matlab.
Simulation results show that the Fuzzy Logic Controllers are far
more superior compared to PID controllers in terms of overshoot,
settling time and response to parameter changes.
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.
Similar to Mathematical Modeling and Fuzzy Adaptive PID Control of Erection Mechanism (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
This document describes using a snake optimization algorithm to tune the gains of an enhanced proportional-integral controller for congestion avoidance in a TCP/AQM system. The controller aims to maintain a stable and desired queue size without noise or transmission problems. A linearized model of the TCP/AQM system is presented. An enhanced PI controller combining nonlinear gain and original PI gains is proposed. The snake optimization algorithm is then used to tune the parameters of the enhanced PI controller to achieve optimal system performance and response. Simulation results are discussed showing the proposed controller provides a stable and robust behavior for congestion control.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Mechatronics is a multidisciplinary field that refers to the skill sets needed in the contemporary, advanced automated manufacturing industry. At the intersection of mechanics, electronics, and computing, mechatronics specialists create simpler, smarter systems. Mechatronics is an essential foundation for the expected growth in automation and manufacturing.
Mechatronics deals with robotics, control systems, and electro-mechanical systems.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Supermarket Management System Project Report.pdfKamal Acharya
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.
Height and depth gauge linear metrology.pdfq30122000
Height gauges may also be used to measure the height of an object by using the underside of the scriber as the datum. The datum may be permanently fixed or the height gauge may have provision to adjust the scale, this is done by sliding the scale vertically along the body of the height gauge by turning a fine feed screw at the top of the gauge; then with the scriber set to the same level as the base, the scale can be matched to it. This adjustment allows different scribers or probes to be used, as well as adjusting for any errors in a damaged or resharpened probe.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
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The structure of this paper is arranged as follows. Model of the electro-hydraulic system
is derived in section 2.1. Kinetic analysis of erection mechanism is accomplished in section 2.2.
The relationships of erection force, erection angle and the length of hydraulic cylinder are
obtained. Fuzzy adaptive PID controller is designed which is composed of fuzzy algorithm and
PID control method in section 3. Models of erection system and fuzzy adaptive controller are
established in Simulink in section 4. Experimental studies are completed on laboratory
equipment in section 5. The control effect of fuzzy adaptive PID controller is validated on
erection mechanism based on simulation and experiment.
2. Mathematical Modeling of Erection System
2.1. Model of the Electro-Hydraulic System
Erection mechanism is mainly composed of hydraulic system and mechanical system.
Mathematical models of each system are established separately. Hydraulic principle of erection
system is shown in Figure 1. It is mainly composed of pump 1, motor 2, relief valve 3, electro-
hydraulic proportional valve 4 and hydraulic cylinder 5.
Figure 1. Hydraulic Principle of Erection System
The pump model can be built by the following equation.
p p p vQ D w (1)
Where Qp is the output flow rate. Dp represents the displacement and ηv is the volumetric
efficiency of pump. wp illustrates the rotational velocity of motor.
The model of electro-hydraulic proportional directional valve is expressed by the
following formulas.
1
1
2( )s
d x
p p
q C A
(2)
2
2
2
d y
p
q C A
(3)
Where q1 and q2 are the flow rate from and to cylinder. Cd represents the flow coefficient of
valve. Ax and Ay are the areas of spool valve. ps is the supply pressure. p1 is the pressure of
piston chamber. p2 is the pressure of piston rod chamber. ρ represents the density of fluid.
The flow and pressure models of hydraulic cylinder are established using the chamber
node method. The dynamic equation is described utilizing the second Newton’s Law.
5
M 1
4
3
2
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256
01 1 1
1 1 1 2( )ec ic ic
e
V A y dpdy
q A C C p C p
dt dt
( )
(4)
02 2 2
2 2 2 1( )ec ic ic
e
V A y dpdy
q A C C p C p
dt dt
( )
(5)
2
1 1 2 2 2
d y
p A p A m F
dt
(6)
Where A1 and A2 represent the area of two chambers in hydraulic cylinder. y illustrates the
displacement of piston. βe illustrates the fluid bulk modulus. V01 and V02 represent the initial
volume of two chambers. Cic and Cec represent leakage coefficients. p1 and p2 are the pressure
in the forward and return cylinder chambers. m is the mass of load. F represents external force.
2.2. Kinetic Analysis of Erection Mechanism
Mechanical part of erection mechanism is shown in Figure 2. The load revolves around
the point P2 driven by hydraulic cylinder.
Figure 2. Kinetic Model of Erection Mechanism
The following equation is established to describe the force balance model.
2 4 2 5( ) ( )pJ t F t PP G PP (7)
Where J represents the moment of inertia. θ(t) is the rotational angle of load. Fp(t) represents
the output force of hydraulic cylinder. G illustrates the gravity of load.
2 3
2 4 2 2 3 2
3
sin( ( ) )
= sin
P P t
P P OP POP OP
OP
(8)
2 5 2= cos( ( ) )GP P P P t (9)
The relationship of erection angle and cylinder length can be acquired by using cosine
theorem in ΔOP2P3.
2 2 2
2 3 2 3
2 3 2
cos( ( ) )
2
P P OP OP
t
P P OP
(10)
y
x
Fp(t)
G
O
P3
P2
PG
P4
P5
θ(t)
α
β
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3. Fuzzy Adaptive PID Controller Design
The connection of fuzzy logic and PID method can utilized the advantages of the two
algorithms. Fuzzy algorithm is utilized to alter the parameters of PID algorithm based on the
change of system parameters [13]. It can take full advantage of expert experience and good
control effect of PID algorithm. Fuzzy adaptive PID algorithm is adopted in erection process to
enhance control performance.
The differential equation of PID control is expressed as follows [14].
( ) ( ) ( ) ( )D
P
I
TT
u kT K e kT e kT e kT T
T T
(11)
Where u(kT) illustrates the output signal. KP represents the propotional coefficient. e illustrates
the input error signal. k is the sampling number. T is the sampling period. TI represents the
integral coefficient. TD represents the differential coefficient.
The principle of fuzzy adaptive PID controller is depicted in Figure 3. Fuzzy logic
algorithm is utilized to change the parameters of KP, KI and KD. The input parameters of fuzzy
logic are e(t) and ec(t). The output parameters of △KP, △KI and △KD are obtained by fuzzy
inference calculation. The values are respectively added to initial values KP0, KI0 and KD0. The
adaptive adjustment of PID algorithm is realized.
Figure 3. The Principle of Fuzzy Adaptive PID Controller
Figure 4. Membership Function Cure of Input
The input and output parameters are transformed into fuzzy logic values and defined as
seven values: NB, NM, NS, ZO, PS, PM and PB [15]. The domain of error e(t) is defined as [-xe,
xe]. The domain of c(t) is defined as [-xc, xc]. The domain of fuzzy subset is defined as {-6, -5, -4,
-3, -2, -1, 0, 1, 2, 3, 4, 5, 6}.
Triangular shape function is selected as input membership function, as depicted in
Figure 4 [16]. The relationships between e(t), c(t) and KP, KI, KD are summarized through much
operating experience [17].
Electro-hydraulic
proportional valve
Fuzzy
Inference
Module
PK
IK
DK
Fuzzy
PID
controller
de
dt
DefuzzificationFuzzy
rules
0
0
0
P P P
I I I
D D D
K K K
K K K
K K K
ecK
eK
PG
IG
DG
Sensor
Hydraulic
cylinder
E
ECec(t)
e(t)
e(t) u(t)
c(t)
ZO PS PM PB
1.0
NSNMNB
0 2 4 6-2-4-6 e(t)
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258
1. When e(t) is relatively large value, KP should be adopted relatively large value to
speed up the system response and reduce time constant with damping coefficient. KD should be
adopted relatively small value to prevent out of range control at the initial stage. In order to
prevent overshoot, the integral value should be removed.
2. When e(t) is medium value, KP should be adopted relatively small value to minimize
response overshoot. The value of KD is important and should be adopted medium value. The
integral value is supposed to appropriately increase.
3. When e(t) is relatively small value, KP and KI are supposed to adopted relatively
large value to have good steady state and avoid oscillation at equilibrium point. KD is supposed
to be adopted appropriate value.
According to above relationships and the impact of c(t), fuzzy logic rules are obtained in
Table 1 through theoretical analysis.
Table 1. Fuzzy Control Rules
△KP /△KI /△KD
e
NB NM NS ZO PS PM PB
c
NB PB/NB/NS PB/NB/PS PM/NM/PB PM/NM/PB PS/NS/PB ZO/ZO/PM ZO/ZO/NS
NM PB/NB/NS PB/NB/PS PM/NM/PB PS/NS/PM PS/NS/PM ZO/ZO/PS NS/ZO/ZO
NS PM/NB/ZO PM/NM/PS PM/NS/PM PS/NS/PM ZO/ZO/PS NS/PS/PS NS/PS/ZO
ZO PM/NM/ZO PM/NM/PS PS/NS/PS ZO/ZO/PS NS/PS/PS NM/PM/PS NM/PM/ZO
PS PS/NM/ZO PS/NS/ZO ZO/ZO/ZO NS/PS/ZO NS/PS/ZO NM/PM/ZO NM/PB/ZO
PM PS/ZO/NB ZO/ZO/PS NS/PS/NS NM/PS/NS NM/PM/NS NM/PB/NS NB/PB/NB
PB ZO/ZO/NB ZO/ZO/NM NM/PS/NM NM/PM/NM NM/PM/NS NB/PB/NS NB/PB/NB
Take the first rule as an example, the above rule can be interpreted as “if e is NB and c
is NB, then △KP /△KI /△KD are PB/NB/NS”. Mamdani algorithm is introduced as fuzzy
implication relation [18].
( , ) ( )( , )
=min( ( ), ( )) ( ) ( )
R a u A U a u
A a U u A a U u
(12)
Triangular shape function is selected as output membership function, as expressed in
Figure 5 [19].
Figure 5. Membership Function Cure of Output
Centroid is chosen as defuzzification method [20], which calculates the area center of
the fuzzy set membership function curve surrounded by the horizontal coordinate. The
horizontal coordinate value of the center is chosen as the representative value of the fuzzy set.
The horizontal coordinate u0 corresponding to the area center is calculated by the following
formula [21].
0
( )
( )
U
U
A u udu
u
A u du
(13)
ZO PS PM PB
1.0
NSNMNB
0 2 4 6-2-4-6 △KP
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4. Simulation and Results
4.1. Modeling Erection Mechanism in Simulink
Figure 6 illustrates the model of the erection system in Simulink software. The desired
angle signal is simulation input. The pressure and position of hydraulic cylinder are simulation
outputs. The entire model is decomposed into several subsystems blocks such as the ‘source’
model, the ‘pump’ model, the ‘valve/cylinder’ model and the ‘fuzzy adaptive PID controller’
model. The output of the controller is derived to control motion of the valve spool. Position of the
spool influences the nominal flow into cylinder chamber. The nominal flow change will change
the volume and pressure inside both cylinder chambers. Finally, the piston position is affected,
therefore the mechanical mechanism moves driven by cylinder piston. Hence, the performance
of the system is dependent on the output of the controller.
Figure 6. Diagram of Complete Erection Model in Simulink
The ‘source’ model is reference angle trajectory. Composite sine function is selected as
reference erection angle trajectory. θ(t) is expressed by the following equations:
1 0( ) ( ) ( )t s (14)
sin(4 ) 1
0
4 4 8
2 4 1 7
( ) 9cos( )/4
4 3 6 8 8
4 sin(4 2 ) 7
1
4 4 8
k
k
s
k
(15)
Where
2
4 4k .θ0 is initial value and θ1 is terminal value of erection angle. T is erection
time, τ=t/T.
Figure 7 shows the valve controlled hydraulic cylinder sub-block derived from Equations
(1) to (6). The model of control valve is built based on flow equation. The model of hydraulic
cylinder is established based on chamber node method. The pressure p1 and p2 appearing as
derivatives in Equations (4) to (6) are utilized as the states.
Simulink block of fuzzy adaptive PID algorithm is expressed in Figure 8. The model is
established in Figure 3 based on the controller structure.
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260
Figure 7. Simulink Block of Hydraulic Cylinder and Valve
Figure 8. Simulink Block of Fuzzy Adaptive PID Controller
4.2. Simulation Results
The purpose of simulation is to investigate the performance of fuzzy adaptive PID
algorithm for erection system. The simulation results are demonstrated by Simulink software in
this section. The parameter values of erection system are demonstrated in Table 2.
The target of controller is to minimize the error of erection angle and planed angle
reference. The control effects of three controllers are compared by simulation. The simulation
results of erection angle are demonstrated in Figure 9. Erection angle curves are expressed in
Figure 9(a). The error curves of erection angle are expressed in Figure 9(b). The maximum
value of angle error controller by PID is 0.15°. The maximum value of angle error controller by
fuzzy logic is 0.12°. The maximum value of angle error controller by fuzzy adaptive PID is 0.03°.
The angle deviation of fuzzy adaptive PID controller is the smallest obtained from the simulation
results. It has the advantage of both PID and fuzzy logic so the control performance is the best.
Fuzzy adaptive PID algorithm could be adopted in erection system to achieve high accuracy.
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Table 2. Parameter Values for Simulation
Symbol Explanation Value
Cd Discharge coefficient 0.61
e Bulk modulus of hydraulic fluid. 6.85e8 Pa
A1 Area of piston chamber 1.23e-3 m2
A2 Annular area of piston rod chamber 5.91e-4 m2
ρ Fluid density 800 kg/m3
Cic Internal leakage coefficient 3e-11
Cec External leakage coefficient 2e-11
m Equivalent mass 500 kg
Ps Hydraulic supply pressure 2.5e6 Pa
V01 Initial volume of piston chamber 2.4e-3 m3
V02 Initial volume of piston rod chamber 0.0089 m3
2OP The length of 2OP 3.08 m
2 3P P The length of 2 3P P 1.11 m
(a) Simulation Erection Angle of Three Controllers
(b) Simulation Erection Angle Error of Three Controllers
Figure 9. Simulation Results of Erection Angle
5. Experimental Verification
Mechanical constitution of laboratory equipment is shown in Figure 10. It is mainly
composed of erection arm and erection cylinder. Programs of data acquisition and three
designed controllers are completed in LabVIEW software.
The control effects of three controllers are compared by experiment. The experiment
results of erection angle are demonstrated in Figure 11. Erection angle curves are expressed in
Figure 11(a). The error curves of erection angle are expressed in Figure 11(b). The maximum
value of angle error controller by PID is 0.6°. The maximum value of angle error controller by
fuzzy logic is 0.2°. The maximum value of angle error controller by fuzzy adaptive PID is
0.1°.From the results we can obtain that the angle deviation of PID is the largest. The angle
deviation of fuzzy logic fluctuates wildly. The tracking deviation of fuzzy adaptive PID is small
0 10 20 30 40 50 60 70 80 90
0
20
40
60
80
100
Time(s)
Angle(deg)
Fuzzy adaptive PID
PID
Fuzzy logic
Desired angle
0 10 20 30 40 50 60 70 80 90
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0.25
Time(s)
Angle(deg)
Fuzzy adaptive PID
PID
Fuzzy logic
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and steady. The experiment results illustrate that fuzzy adaptive PID control could be applied in
erection system.
Figure 10. Mechanical Constitution of the Platform
(a) Experiment Erection Angle of Three Controllers
(b) Experiment Erection Angle Error of Three Controllers
Figure 11. Experiment Results of Erection Angle
6. Conclusion
Mathematical model of electro-hydraulic system was derived. Kinetic model of erection
mechanism was established. Fuzzy adaptive PID algorithm was applied to erection mechanism
in combination of fuzzy logic and PID algorithm. The model of erection system was established
in Simulink. The simulation and experiment results of three control algorithms were compared
and verified. From the results, it is obviously obtained that fuzzy adaptive PID algorithm has the
best control effect. Hence the designed algorithm could be applied in erection system to achieve
high control accuracy.
0 10 20 30 40 50 60 70 80 90
0
20
40
60
80
100
Time(s)
Angle(deg)
Fuzzy adaptive PID
PID
Fuzzy logic
Desired angle
0 10 20 30 40 50 60 70 80 90
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
Time(s)
Angle(deg)
Fuzzy adaptive PID
PID
Fuzzy logic
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Acknowledgement
This research was financially supported by the National Natural Science Foundation of
China (Grant No. 51475462).
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