Controllers -Controller is a device that takes a decision in order to maintain the steady state of the system on the basis of error signal.
Controllers are the need of the controls system
To supress the effect of external disturbance in order to maintain the steady state
To maintain the stability of the system.
To optimize the process in order to increase the profits.
Error signals are input to the controller.
Controller takes decision in the form of decision signal as ideal valve opening and hence corresponding air pressure is given in the form pneumatic signal.
Error = hsp -h = Setpoint variable (Controlled variable) – Measured variable.
Decision signal is in terms of pneumatic signal to the valve.
1.Liquid level control – Proportional action Controller (P action)
2.Gas pressure control - Proportional action Controller (P action)
3.Vapor pressure control –
For fast response PI controller , for slow response PID controller.
4. Flow Conrol-Proportional Integral Controller (PI action)
5. Temperature control – Proportional integral derivative controller (PID action)
6. Composition control – Proportional integral derivative controller (PID action)
In this Seminar report I mentioned all types of controllers that used in chemical industries for various purpose.
Controllers are need of control system to control different types of process and operation in the plant so it is difficult to choose controllers because it reduces effort and gives safety to the plant so in this seminar report i study important examples in which controllers are used.
I also mentioned introduction of control loop because its helps us to understand the behavior of controller in process.
The document discusses PID controllers, which are commonly used in industrial control systems. It describes the five main modes of PID control: on-off, proportional (P), proportional-integral (PI), proportional-derivative (PD), and proportional-integral-derivative (PID). The PID controller combines proportional, integral, and derivative actions to provide stable system response without steady-state error for various process control applications. Design of a PID controller involves tuning the proportional, integral, and derivative gains to achieve the desired closed-loop response.
The document discusses PID controllers, including:
1) PID controllers use proportional, integral and derivative modes to control systems. The proportional mode determines how much correction is made, the integral mode determines how long a correction is applied, and the derivative mode determines how fast a correction is made.
2) Ziegler-Nichols tuning rules provide methods to experimentally determine PID parameters (Kp, Ti, Td) when mathematical models are unknown, including open-loop and closed-loop methods using a plant's step response.
3) An electronic PID controller can be implemented as a circuit using resistors and capacitors to realize the proportional, integral and derivative terms.
This document provides an overview of PID controllers, including:
- The three components of a PID controller are proportional, integral, and derivative terms.
- PID controllers are widely used in industrial control systems due to their general applicability even without a mathematical model of the system.
- Ziegler-Nichols tuning rules can be used to experimentally determine initial PID parameters to provide a stable initial response for the system. Fine-tuning is then used to optimize the response.
control technology of bachlor of engineering technologyengineerfazi245
This document is a lecture on PID controllers that discusses:
- PID controllers are widely used in industrial control systems to regulate variables like temperature, pressure, and level.
- A PID controller calculates the error between a setpoint and measured process variable, and determines the necessary adjustments to the control input based on proportional, integral and derivative terms.
- The lecture provides background on PID controllers and explains the individual proportional, integral and derivative terms and how they work together to provide accurate and stable control.
Automatic process control systems are needed because industrial processes are dynamic and continuously changing due to disturbances. Control systems continuously monitor and automatically adjust important process variables like temperature, pressure, and flow. They provide benefits like enhanced safety, meeting quality standards, efficient use of resources, and increased profits. A basic control system works by measuring process variables, making decisions based on the measurements, and taking action by adjusting manipulative variables.
Basics On Process Control and PID's.pdfboyrindrawan1
This document discusses process control and PID controllers. It describes seven objectives of process control including safety, environmental protection, and profit. It defines different types of controllers including on-off, proportional, proportional-integral, proportional-derivative, and proportional-integral-derivative controllers. It also explains feedback and feedforward control systems and how they differ in their approach to disturbances. Finally, it briefly introduces cascade, ratio, and split control systems.
Module 1 discusses process control concepts including mathematical models of processes, control actions, and controller modes. It describes first and higher order processes, interacting and non-interacting systems, and continuous and batch processes. The basic control actions of on-off, proportional, integral, and derivative control modes are covered as well as combined P+I, P+D, and P+I+D control modes. Both pneumatic and electronic controllers used to realize various control actions are introduced.
The document discusses PID controllers, which are commonly used in industrial control systems. It describes the five main modes of PID control: on-off, proportional (P), proportional-integral (PI), proportional-derivative (PD), and proportional-integral-derivative (PID). The PID controller combines proportional, integral, and derivative actions to provide stable system response without steady-state error for various process control applications. Design of a PID controller involves tuning the proportional, integral, and derivative gains to achieve the desired closed-loop response.
The document discusses PID controllers, including:
1) PID controllers use proportional, integral and derivative modes to control systems. The proportional mode determines how much correction is made, the integral mode determines how long a correction is applied, and the derivative mode determines how fast a correction is made.
2) Ziegler-Nichols tuning rules provide methods to experimentally determine PID parameters (Kp, Ti, Td) when mathematical models are unknown, including open-loop and closed-loop methods using a plant's step response.
3) An electronic PID controller can be implemented as a circuit using resistors and capacitors to realize the proportional, integral and derivative terms.
This document provides an overview of PID controllers, including:
- The three components of a PID controller are proportional, integral, and derivative terms.
- PID controllers are widely used in industrial control systems due to their general applicability even without a mathematical model of the system.
- Ziegler-Nichols tuning rules can be used to experimentally determine initial PID parameters to provide a stable initial response for the system. Fine-tuning is then used to optimize the response.
control technology of bachlor of engineering technologyengineerfazi245
This document is a lecture on PID controllers that discusses:
- PID controllers are widely used in industrial control systems to regulate variables like temperature, pressure, and level.
- A PID controller calculates the error between a setpoint and measured process variable, and determines the necessary adjustments to the control input based on proportional, integral and derivative terms.
- The lecture provides background on PID controllers and explains the individual proportional, integral and derivative terms and how they work together to provide accurate and stable control.
Automatic process control systems are needed because industrial processes are dynamic and continuously changing due to disturbances. Control systems continuously monitor and automatically adjust important process variables like temperature, pressure, and flow. They provide benefits like enhanced safety, meeting quality standards, efficient use of resources, and increased profits. A basic control system works by measuring process variables, making decisions based on the measurements, and taking action by adjusting manipulative variables.
Basics On Process Control and PID's.pdfboyrindrawan1
This document discusses process control and PID controllers. It describes seven objectives of process control including safety, environmental protection, and profit. It defines different types of controllers including on-off, proportional, proportional-integral, proportional-derivative, and proportional-integral-derivative controllers. It also explains feedback and feedforward control systems and how they differ in their approach to disturbances. Finally, it briefly introduces cascade, ratio, and split control systems.
Module 1 discusses process control concepts including mathematical models of processes, control actions, and controller modes. It describes first and higher order processes, interacting and non-interacting systems, and continuous and batch processes. The basic control actions of on-off, proportional, integral, and derivative control modes are covered as well as combined P+I, P+D, and P+I+D control modes. Both pneumatic and electronic controllers used to realize various control actions are introduced.
The document discusses PID controllers, which are widely used in 95% of industrial controllers. PID controllers combine proportional, integral, and derivative actions to achieve fast response, zero steady state error, and less overshoot. The PID controller calculates proportional, integral, and derivative values based on the error between the measured process variable and desired setpoint. By combining these three control modes, the PID controller can control processes very well through its ability to respond to present, past, and future errors.
The document discusses proportional (P) control and its limitations. A P-only controller can reduce fluctuations but cannot eliminate steady-state error or offset. Adding an integral (I) term can eliminate offset by incorporating past errors, but higher I gain can cause instability. The document examines examples of P-only control response and how adding I improves response while reducing overshoot and oscillations. However, carefully tuning the gains is necessary for stability.
The document discusses various aspects of control systems including proportional, integral and derivative control actions. It describes how proportional, PI, PD and PID controllers work and their effects on transient response specifications like percentage overshoot, rise time, settling time and steady state error. PID controllers can be implemented in parallel or series form, with the series form being more commonly used in industry. Manual tuning of PID controllers involves adjusting the P, I, and D gains to achieve the desired closed-loop response.
The document discusses various aspects of control systems including proportional, integral and derivative control actions. It describes how proportional, PI, PD and PID controllers work and their effects on transient response specifications like percentage overshoot, rise time, settling time and steady state error. PID controllers can be implemented in parallel or series form, with the series form being more commonly used in industry. Manual tuning of PID controllers involves adjusting the P, I, and D gains to achieve the desired closed-loop response.
The document describes various controller modes including:
1. ON-OFF/two position controller - provides discontinuous control by switching between maximum and minimum output values.
2. Proportional (P) control - controller output is proportional to the error. Provides fast response but steady state error.
3. Integral (I) control - controller output is proportional to the integral of error over time. Eliminates steady state error but increases response time.
4. Derivative (D) control - controller output is proportional to the rate of change of error. Increases damping but can amplify noise and cause instability.
Composite modes like PI, PD, and PID combine the advantages of the individual modes to provide
Three control loops are described: open loop control which takes action without feedback, closed loop control which measures process variables, compares to setpoints, and adjusts to correct deviations, and proportional control which adjusts the correcting element proportionally to the error. Key aspects of proportional, integral, and derivative control modes are also summarized. Proportional control responds directly to error, integral control eliminates offset through repeated proportional action, and derivative control improves response in slow processes by anticipating needed output changes.
1. The document discusses different types of controllers used in industrial processes including proportional (P), integral (I), derivative (D), PI, PID, and their basic concepts and circuit diagrams.
2. Analog controllers use operational amplifiers as building blocks and provide advantages like compact size, fast response, high reliability and accuracy.
3. PID controllers combine proportional, integral and derivative actions to provide fast response, zero steady-state error and ensure stable system operation, though their optimization can be complex. PID controllers are commonly used for temperature and pressure control.
This document provides an overview of control systems and PID controllers. It discusses the different control actions of proportional (P), integral (I), and derivative (D) control and how they each affect characteristics like rise time, overshoot, and steady state error. PID controllers are widely used to control industrial processes and provide stable regulation. The document outlines manual tuning procedures for PID controllers by first implementing P, then adding D to reduce overshoot and I to eliminate steady state error. PID controllers are useful for regulating processes like flow, temperature, pressure as well as motion control applications.
This document provides an overview of different approaches for tuning PID controllers. It first introduces PID controllers and their proportional, integral and derivative terms. It then describes several common methods for tuning PID controllers, including manual tuning on-site, Ziegler-Nichols reaction curve method, Ziegler-Nichols oscillation method, and Cohen-Coon method. These tuning methods are compared based on their performance and applicability to different process control systems.
The document discusses different types of process controllers and their time responses. It explains that proportional (P), integral (I), derivative (D) and combined PI, PD, and PID controllers each have different effects on how the manipulated variable is calculated from the system deviation over time. It also discusses cascade, feedforward and ratio control systems which complement basic feedback control loops.
This document discusses fundamental control theory concepts. It introduces control systems and defines them as systems that control an output to a particular value, sequence, or event based on inputs. Open and closed loop systems are described, with closed loop utilizing feedback to correct errors. The basic elements of open and closed loop systems are also outlined, including the comparison element, control law implementation element, correction element, process, and measurement element. Finally, motor shaft speed control is provided as a case study example.
Okay, let's solve this step-by-step:
* Set point (Io) = 12 rpm
* Range = 15 - 10 = 5 rpm
* Initial controller output = 22%
* KI = -0.15%/s/% error
* Error = Actual - Set point = ?
* Given: Initial output is 22%
* To find: What is the actual speed?
Using the integral control equation:
Iout = Io - KI * ∫edt
22% = 12rpm - 0.15%/s/% * ∫e dt
∫e dt = (22% - 12rpm)/0.15%/s/% = 40%*
This document discusses tuning PID controllers. It introduces PID controllers and their proportional, integral and derivative terms. It describes different tuning methods, focusing on the Ziegler-Nicolas tuning method. This method relates process parameters like delay time and gain to PID parameters. It involves adjusting the proportional band until oscillations occur, then using those values to calculate initial PID settings according to provided tables. The goal of tuning is to optimize rise time, overshoot, settling time, steady state error and stability.
This document discusses various process control concepts including controller modes and actions. It describes:
- Proportional, integral, and derivative control modes and how they work individually. The proportional mode reduces error but causes offset. Integral mode eliminates offset but can cause overshoot. Derivative mode responds to the rate of error change.
- Composite control modes like PI, PD, and PID that combine the individual modes. PI eliminates offset and handles load changes. PD handles fast changes but does not remove offset. PID is most powerful but complex.
- Issues like integral windup where the integral term grows unchecked and causes control loss must be addressed using techniques like back-calculation or clamping.
The document provides an overview of advanced process control (APC), including its definition, applications, advantages, and limitations. It discusses how APC builds on basic process control techniques by using process models and optimization to enhance plant operation and profitability. Examples are given of APC applications in petrochemical plants and semiconductor manufacturing. The benefits of APC include improved yield, quality, energy efficiency, and responsiveness. However, APC implementations are also complex, time-consuming, and require specialized expertise and resources.
The document discusses different types of controllers used in industrial control systems:
1. Proportional, integral, and proportional-integral controllers which reduce steady state error but can increase oscillations.
2. Derivative and proportional-derivative controllers which reduce overshoot and oscillations but do not affect steady state response.
3. Proportional-integral-derivative (PID) controllers which are most commonly used as they calculate error based on proportional, integral, and derivative terms to minimize error over time.
The effects of changing gains for each controller type are also summarized, such as increasing gain reducing steady state error but potentially decreasing stability.
This document discusses P, PI, and PID controllers. P controllers use proportional control to reduce error, but can still have steady state error. PI controllers add integral control to eliminate steady state error, at the cost of increased overshoot. PID controllers further add derivative control to increase stability by reducing overshoot. The output of a PID controller is the sum of proportional, integral, and derivative responses to the error between the measured and desired set point values.
The document discusses PID controllers, which are widely used in 95% of industrial controllers. PID controllers combine proportional, integral, and derivative actions to achieve fast response, zero steady state error, and less overshoot. The PID controller calculates proportional, integral, and derivative values based on the error between the measured process variable and desired setpoint. By combining these three control modes, the PID controller can control processes very well through its ability to respond to present, past, and future errors.
The document discusses proportional (P) control and its limitations. A P-only controller can reduce fluctuations but cannot eliminate steady-state error or offset. Adding an integral (I) term can eliminate offset by incorporating past errors, but higher I gain can cause instability. The document examines examples of P-only control response and how adding I improves response while reducing overshoot and oscillations. However, carefully tuning the gains is necessary for stability.
The document discusses various aspects of control systems including proportional, integral and derivative control actions. It describes how proportional, PI, PD and PID controllers work and their effects on transient response specifications like percentage overshoot, rise time, settling time and steady state error. PID controllers can be implemented in parallel or series form, with the series form being more commonly used in industry. Manual tuning of PID controllers involves adjusting the P, I, and D gains to achieve the desired closed-loop response.
The document discusses various aspects of control systems including proportional, integral and derivative control actions. It describes how proportional, PI, PD and PID controllers work and their effects on transient response specifications like percentage overshoot, rise time, settling time and steady state error. PID controllers can be implemented in parallel or series form, with the series form being more commonly used in industry. Manual tuning of PID controllers involves adjusting the P, I, and D gains to achieve the desired closed-loop response.
The document describes various controller modes including:
1. ON-OFF/two position controller - provides discontinuous control by switching between maximum and minimum output values.
2. Proportional (P) control - controller output is proportional to the error. Provides fast response but steady state error.
3. Integral (I) control - controller output is proportional to the integral of error over time. Eliminates steady state error but increases response time.
4. Derivative (D) control - controller output is proportional to the rate of change of error. Increases damping but can amplify noise and cause instability.
Composite modes like PI, PD, and PID combine the advantages of the individual modes to provide
Three control loops are described: open loop control which takes action without feedback, closed loop control which measures process variables, compares to setpoints, and adjusts to correct deviations, and proportional control which adjusts the correcting element proportionally to the error. Key aspects of proportional, integral, and derivative control modes are also summarized. Proportional control responds directly to error, integral control eliminates offset through repeated proportional action, and derivative control improves response in slow processes by anticipating needed output changes.
1. The document discusses different types of controllers used in industrial processes including proportional (P), integral (I), derivative (D), PI, PID, and their basic concepts and circuit diagrams.
2. Analog controllers use operational amplifiers as building blocks and provide advantages like compact size, fast response, high reliability and accuracy.
3. PID controllers combine proportional, integral and derivative actions to provide fast response, zero steady-state error and ensure stable system operation, though their optimization can be complex. PID controllers are commonly used for temperature and pressure control.
This document provides an overview of control systems and PID controllers. It discusses the different control actions of proportional (P), integral (I), and derivative (D) control and how they each affect characteristics like rise time, overshoot, and steady state error. PID controllers are widely used to control industrial processes and provide stable regulation. The document outlines manual tuning procedures for PID controllers by first implementing P, then adding D to reduce overshoot and I to eliminate steady state error. PID controllers are useful for regulating processes like flow, temperature, pressure as well as motion control applications.
This document provides an overview of different approaches for tuning PID controllers. It first introduces PID controllers and their proportional, integral and derivative terms. It then describes several common methods for tuning PID controllers, including manual tuning on-site, Ziegler-Nichols reaction curve method, Ziegler-Nichols oscillation method, and Cohen-Coon method. These tuning methods are compared based on their performance and applicability to different process control systems.
The document discusses different types of process controllers and their time responses. It explains that proportional (P), integral (I), derivative (D) and combined PI, PD, and PID controllers each have different effects on how the manipulated variable is calculated from the system deviation over time. It also discusses cascade, feedforward and ratio control systems which complement basic feedback control loops.
This document discusses fundamental control theory concepts. It introduces control systems and defines them as systems that control an output to a particular value, sequence, or event based on inputs. Open and closed loop systems are described, with closed loop utilizing feedback to correct errors. The basic elements of open and closed loop systems are also outlined, including the comparison element, control law implementation element, correction element, process, and measurement element. Finally, motor shaft speed control is provided as a case study example.
Okay, let's solve this step-by-step:
* Set point (Io) = 12 rpm
* Range = 15 - 10 = 5 rpm
* Initial controller output = 22%
* KI = -0.15%/s/% error
* Error = Actual - Set point = ?
* Given: Initial output is 22%
* To find: What is the actual speed?
Using the integral control equation:
Iout = Io - KI * ∫edt
22% = 12rpm - 0.15%/s/% * ∫e dt
∫e dt = (22% - 12rpm)/0.15%/s/% = 40%*
This document discusses tuning PID controllers. It introduces PID controllers and their proportional, integral and derivative terms. It describes different tuning methods, focusing on the Ziegler-Nicolas tuning method. This method relates process parameters like delay time and gain to PID parameters. It involves adjusting the proportional band until oscillations occur, then using those values to calculate initial PID settings according to provided tables. The goal of tuning is to optimize rise time, overshoot, settling time, steady state error and stability.
This document discusses various process control concepts including controller modes and actions. It describes:
- Proportional, integral, and derivative control modes and how they work individually. The proportional mode reduces error but causes offset. Integral mode eliminates offset but can cause overshoot. Derivative mode responds to the rate of error change.
- Composite control modes like PI, PD, and PID that combine the individual modes. PI eliminates offset and handles load changes. PD handles fast changes but does not remove offset. PID is most powerful but complex.
- Issues like integral windup where the integral term grows unchecked and causes control loss must be addressed using techniques like back-calculation or clamping.
The document provides an overview of advanced process control (APC), including its definition, applications, advantages, and limitations. It discusses how APC builds on basic process control techniques by using process models and optimization to enhance plant operation and profitability. Examples are given of APC applications in petrochemical plants and semiconductor manufacturing. The benefits of APC include improved yield, quality, energy efficiency, and responsiveness. However, APC implementations are also complex, time-consuming, and require specialized expertise and resources.
The document discusses different types of controllers used in industrial control systems:
1. Proportional, integral, and proportional-integral controllers which reduce steady state error but can increase oscillations.
2. Derivative and proportional-derivative controllers which reduce overshoot and oscillations but do not affect steady state response.
3. Proportional-integral-derivative (PID) controllers which are most commonly used as they calculate error based on proportional, integral, and derivative terms to minimize error over time.
The effects of changing gains for each controller type are also summarized, such as increasing gain reducing steady state error but potentially decreasing stability.
This document discusses P, PI, and PID controllers. P controllers use proportional control to reduce error, but can still have steady state error. PI controllers add integral control to eliminate steady state error, at the cost of increased overshoot. PID controllers further add derivative control to increase stability by reducing overshoot. The output of a PID controller is the sum of proportional, integral, and derivative responses to the error between the measured and desired set point values.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
6th International Conference on Machine Learning & Applications (CMLA 2024)
Use of different types of Controllers in Chemical Industry.pptx
1. Dr. BABASAHEB AMBEDKAR TECHNOLOGICAL UNIVERSITY
Lonere, Mangaon, 402104
2021-2022
MINI PROJECT -
Use of different types of controllers in chemical industry.
SUBMITTED BY - KETAN PRASHANT KULKARNI
PRN-1930331507009
UNDER GUIDANCE OF – PROF Y.S.MAHAJAN
2. INTRODUCTION
• Controllers -Controller is a device that takes a decision in order to maintain the steady state of the
system on the basis of error signal.
• Controllers are the need of the controls system
• To supress the effect of external disturbance in order to maintain the steady state
• To maintain the stability of the system.
• To optimize the process in order to increase the profits.
• Error signals are input to the controller.
• Controller takes decision in the form of decision signal as ideal valve opening and hence
corresponding air pressure is given in the form pneumatic signal.
• Error = hsp -h = Setpoint variable (Controlled variable) – Measured variable.
• Decision signal is in terms of pneumatic signal to the valve.
3. Input and output variables
• Input variables :
• The variables that can change the output
variable/controlled variables .
• It is a variable which we give to the system to
change the output
• They are of two types : -
• Manipulated variable
• The variables whose values can be adjusted by
any human operator or by any controller.
• Disturbance variable
• The variables whose values cannot be adjusted
by any human operator or by any controller.
• Output variables :
• The Variables that we want to control is
known as output variable or controlled
variable
• They are of two types
• Measured output variable
• The output variable that can be
measured cheapily , effectively and
accurately.
• Unmeasured output variable
• The output variable that can not be
measured cheapily , effectively and
accurately.
4. Proportional Action controller
• Proportional control is a form of feedback control. It is the simplest form
of continuous control that can be used in a closed-looped system.
• c(s) = Kc.e(S),
• P action does not change the nature of the signal. If the input signal is
step then output signal will also be step.
• P-action is a zero order system.
• If we add P-action with a 1st order process then the overall order of the
system will be first order.
• P-action always works on the basis of present error.
• Disadvantage :
• For a very small change in the error signal.P-action does not work well and
unable to work because of which that error value persist in the system and
we will never be able to achieve the orginal steady state .
• Proportional Band (PB)
• Range of the error signal required to
move the valve from fully open to fully
closed condition.
• Kc∝ (1/ PB)
• As controllers gain increases , offset
decreases, so if Kc increased then the
range of proportional band will
decrease or error signal range will
decrease.
• Every P action can’t be on-off action
for that short time solution is that by
increasing value Kc then value of error
signal range will decrease.
5. Integral and Derivative action controller
• Integral control is a second form of feedback
control. It is often used because it is able to
remove any deviations that may exist.
• I action controller always works on the basis
of past error.
• I action completely reduces offset to zero
• I action controllers affect the system by
responding to accumulated past error.
D-control correlates the controller output to the
derivative of the error.
D action controller always works on the basis of
future error.
D-control is a form of feed forward control. D-
control anticipates the process conditions by
analyzing the change in error
6. Proportional integral action controller
• PI control is a form of feedback control. It provides a faster response time than I-only control due to the
addition of the proportional action.
• PI action is of 1st order and that’s why they are slower than P-action.
• PI Action changes the nature of the input signals. If error signal is step then PI action changes the
nature to ramp.
• In P-action along with I action together produces response even for very small change in error signal
and this response is able to move the valve which in turn reduces the offset to zero
• Disadvantage-
• In the case of PI Action, we use to store the error signal magnitude in the storage device But like every
storage device, this one also get full after some time and that's why need a reset. That is why PI action
also known as Reset Action Controller.
• Because of reset, controller's setting also got erased. That is why tuning is required. In In tuning, we
calculate the value of controller's parameter and set them along with many other settings. This tuning
process can be manual or even automatic these days.
7. Proportional Derivative action controller
• PD-control is combination of feedforward and feedback control, because it operates on both the
current process conditions and predicted process conditions.
• In PD-control, the control output is a linear combination of the error signal and its derivative.
• The Main problem of P action is Offset and that Can be eliminated by I Action. But if we use D-
Action along with P-Action then it may become more faster but the problem of offset will remain
as it is D-Action does not eliminate offset.
• That is why PD Action is not in use in chemical engineering practices.
8. Proportional Integral derivative controller
• PID action exhibits 1st order dynamics.
• PID action just like the PI action are slower than P-action but in some cases it can be fast
• Proportional-integral-derivative control is a combination of all three types of control methods.
• PID-control is most commonly used because it combines the advantages of each type of control. This
includes a quicker response time because of the P control, along with the decreased/zero offset from the
combined derivative and integral controllers.
• This offset was removed by additionally using the I-control. The addition of D-control greatly increases the
controller's response when used in combination because it predicts disturbances to the system by measuring
the change in error
• In PID controller past , present and future errors and disturbances are solved.
• PID action just like the PI action changes the nature of the input signal. Means step change in error signal
results in ramp change in the response.
• Offset in this case of PID action is zero just like the PI action because of the presence of I action in both the
actions
9. Drawbacks of PID controller
Derivative Windup
• Because of the use of derivative control, PID control cannot be used in processes where there is a lot
of noise, since the noise would interfere with the predictive, feedforward aspect.
• Thus a bounded and stable response becomes unstable and unbounded response .It caused by D –
action so it is known as derivative windup
• Just like the PI Action , PID action also known as Reset action and tuning is required after the reset.
10. Examples in which controllers are used
1.Liquid level control – Proportional action Controller (P action)
2.Gas pressure control - Proportional action Controller (P action)
3.Vapor pressure control –
For fast response PI controller , for slow response PID controller.
4. Flow Conrol-Proportional Integral Controller (PI action)
5. Temperature control – Proportional integral derivative controller (PID action)
6. Composition control – Proportional integral derivative controller (PID action)
•
11. Conclusion
• In this Seminar report I mentioned all types of controllers that used in
chemical industries for various purpose.
• Controllers are need of control system to control different types of process
and operation in the plant so it is difficult to choose controllers because it
reduces effort and gives safety to the plant so in this seminar report i study
important examples in which controllers are used.
• I also mentioned introduction of control loop because its helps us to
understand the behavior of controller in process.