scholarly journals Quadratic Model-Based Dynamically Updated PID Control of CSTR System with Varying Parameters

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 31
Author(s):  
Dushko Stavrov ◽  
Gorjan Nadzinski ◽  
Stojche Deskovski ◽  
Mile Stankovski
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Absolute Error ◽  
Error Model ◽  
Quadratic Model ◽  
Control Performance ◽  
Continuous Stirred Tank Reactor ◽  
Quadratic Error ◽  
Varying Parameters ◽  
Cstr System

In this paper, we discuss an improved version of the conventional PID (Proportional–Integral–Derivative) controller, the Dynamically Updated PID (DUPID) controller. The DUPID is a control solution which preserves the advantages of the PID controller and tends to improve them by introducing a quadratic error model in the PID control structure. The quadratic error model is constructed over a window of past error points. The objective is to use the model to give the conventional PID controller the awareness needed to battle the effects caused by the variation of the parameters. The quality of the predictions that the model is able to deliver depends on the appropriate selection of data used for its construction. In this regard, the paper discusses two algorithms, named 1D (one dimensional) and 2D (two dimensional) DUPID. Appropriate to their names, the former selects data based on one coordinate, whereas the latter selects the data based on two coordinates. Both these versions of the DUPID controller are compared to the conventional PID controller with respect to their capabilities of controlling a Continuous Stirred Tank Reactor (CSTR) system with varying parameters in three different scenarios. As a quantifying measure of the control performance, the integral of absolute error (IAE) metric is used. The results from the performed simulations indicated that the two versions of the DUPID controller improved the control performance of the conventional PID controller in all scenarios.

scholarly journals Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
A. Jayachitra ◽  
R. Vinodha
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Absolute Error ◽  
Stirred Tank ◽  
Continuous Stirred Tank Reactor ◽  
Stirred Tank Reactor ◽  
Tank Reactor ◽  
Operating Range ◽  
Continuous Stirred Tank ◽  
Dynamic Nonlinearity

Genetic algorithm (GA) based PID (proportional integral derivative) controller has been proposed for tuning optimized PID parameters in a continuous stirred tank reactor (CSTR) process using a weighted combination of objective functions, namely, integral square error (ISE), integral absolute error (IAE), and integrated time absolute error (ITAE). Optimization of PID controller parameters is the key goal in chemical and biochemical industries. PID controllers have narrowed down the operating range of processes with dynamic nonlinearity. In our proposed work, globally optimized PID parameters tend to operate the CSTR process in its entire operating range to overcome the limitations of the linear PID controller. The simulation study reveals that the GA based PID controller tuned with fixed PID parameters provides satisfactory performance in terms of set point tracking and disturbance rejection.

Design of Gain Scheduled Multivariable Controllers for a Nonlinear Process

2011 ◽  
Vol 403-408 ◽  
pp. 4821-4827 ◽  
Author(s):  
N. Kamala ◽  
T. Thyagarajan ◽  
S. Renganathan
Keyword(s):  
Pid Controller ◽  
Absolute Error ◽  
Nonlinear Process ◽  
Simulation Studies ◽  
Continuous Stirred Tank Reactor ◽  
Control Scheme ◽  
Continuous Stirred Tank ◽  
Dynamic Nonlinearity ◽  
Gain Scheduled ◽  
Operating Points

In this paper, Genetic Algorithm is utilized to optimize the coefficients of a decentralized PID controller for a nonlinear Multi-Input Multi-output process by minimizing the Integral Absolute Error (IAE).The controller is tuned at chosen operating points, which are selected to cover the nonlinear range of the process. The optimal PID controller parameters are gain scheduled using a Fuzzy Gain scheduler. The effectiveness of the proposed control scheme has been demonstrated by conducting simulation studies on a Continuous Stirred Tank Reactor (CSTR) process which exhibits dynamic nonlinearity

scholarly journals Kalman Filter to Improve Performance of PID Control Systems on DC Motors

2021 ◽  
Vol 5 (3) ◽  
pp. 96
Author(s):  
Seta Yuliawan ◽  
Oyas Wahyunggoro ◽  
Nurman Setiawan
Keyword(s):  
Kalman Filter ◽  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Absolute Error ◽  
Pid Controllers ◽  
Electronic Components ◽  
Improve Performance ◽  
Noise Sources ◽  
Dc Motors

A proportional–integral–derivative (PID) controller is a type of control system that is most widely applied in industrial world. Various tuning models have been developed to obtain optimal performance in PID control. However, the methods are designed under ideal circumstances. This means that the control system which has been built will not work optimally when noise exists. Noise can come from electrical vibrations, inference of electronic components, or other noise sources. Thus, it is necessary to design PID control system that can work optimally without being disturbed by noise. In this research, Kalman filter was used to improve the performance of PID controllers. The application of Kalman filter was used to reduce the noise of the input signal so that it could generate output signal which is in accordance with the expected output. Simulation result showed that the PID performance with Kalman filter was more optimal than the ordinary one to minimize the existing noise. The resulting speed of DC motor with Kalman filter had a lower overshoot than PID control without Kalman filter. This method resulted lower integral of absolute error (IAE) than ordinary PID controls. The IAE value for the PID controller with the Kalman filter was 25.4, the PID controller with the observer was 31.0, while the IAE value in the ordinary controller was only 60.9.

Generalized Predictive PID Control for Main Steam Temperature Based on Improved PSO Algorithm

2017 ◽  
Vol 21 (3) ◽  
pp. 507-517 ◽  
Author(s):  
Zhongda Tian ◽  
◽  
Shujiang Li ◽  
Yanhong Wang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Particle Swarm Optimization Algorithm ◽  
System Control ◽  
Pd Controller ◽  
Control Performance ◽  
Control Loop ◽  
Steam Temperature ◽  
Swarm Optimization ◽  
Main Steam

The large inertia and long delay characteristics of main steam temperature control system in thermal power plants will reduce the system control performance. In order to improve the system control performance, a generalized predictive PID control for main steam temperature strategy based on improved particle swarm optimization algorithm is proposed. The performance index of incremental PID controller of main control loop and PD controller of auxiliary control loop based on generalized predictive control algorithm is established. An improved particle swarm optimization algorithm with better fitness and faster convergence speed is proposed for online parameters optimization of performance index. The optimal control value of PID controller and PD controller can be obtained. The simulation experiment compared with fuzzy PID and fuzzy neural network is carried out. Simulation results show that proposed control method has faster response speed, smaller overshoot and control error, better tracking performance, and reduces the lag effect of the control system.

Integral Separation PID Control in the Control of Lye Concentration

2012 ◽  
Vol 627 ◽  
pp. 489-493 ◽  
Author(s):  
Liang Huang ◽  
Shi Hai Zhao ◽  
Lin Cui
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
System Simulation ◽  
Dynamic Performance ◽  
Control Performance ◽  
Integral Separation ◽  
Simulation Results

For the requirements of the lye concentration in the mercerizing process, this article is designed for the control of the lye concentration in the integral separation PID controller, the controller is based on conventional PID control, Integral separation, and further improve the performance of the PID controller, improve the accuracy of the lye concentration control system. Simulation results show that: precise characteristics of the controller's existing conventional PID controller, and integral separation PID control system overshoot, improve the dynamic performance of the control system, enables the system to achieve satisfactory control performance.

scholarly journals PID Controller Design Based on Radial Basis Function Neural Networks for the Steam Generator Level Control

2016 ◽  
Vol 16 (5) ◽  
pp. 15-26 ◽  
Author(s):  
Kong Xiangsong ◽  
Chen Xurui ◽  
Guan Jiansheng
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Radial Basis Function ◽  
Steam Generator ◽  
Pid Control ◽  
Basis Function ◽  
Pid Controller ◽  
Rbf Neural Networks ◽  
Control Performance ◽  
Level Control

Abstract Steam generator level control system is a vital control system for the Pressurized Water Reactor (PWR). However, the steam generator level process is a highly nonlinear and non-minimum phase system, the conventional Proportional- Integral-Derivative (PID) control scheme with fixed parameters was difficult to obtain satisfactory control performance. The Radial Basis Function (RBF) Neural Networks based PID control strategy (RBFNN-PID) is proposed for the steam generator level control. This method can identify the mathematical model of the steam generator via the RBF neural networks, and then the PID parameters can be optimized automatically to accommodate the characteristic variation of the process. The optimal number of the hidden layer neurons is also discussed in this paper. The simulation results shows that the PID controller designed based on the RBF neural networks has good control performance on the steam generator level control.

Comparative Analysis of Various Control Strategies for a Nonlinear CSTR System

2017 ◽  
Vol 18 (3-4) ◽  
pp. 269-276
Author(s):  
R. Madhu Sudhanan ◽  
Dr. P. Poongodi
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Control Strategies ◽  
Moving Average ◽  
Nonlinear Process ◽  
Autoregressive Moving Average ◽  
Continuous Stirred Tank Reactor ◽  
Highly Nonlinear ◽  
Nonlinear Temperature ◽  
Cstr System

AbstractContinuous stirred tank reactor (CSTR) is a highly nonlinear process particularly when chemical reaction takes place. The heat energy will be either liberate or absorbed by the reactor due to the reaction. The control of temperature for this process is a real challenge due to nonlinear temperature changes during reaction. In this paper a mathematical model of CSTR with its transfer function is taken for controller design and analysis. The temperature inside the reactor is controlled by altering the coolant jacket temperature. This paper compares the performances of the proportional integral derivative controller (PID) controller, PID-based nonlinear autoregressive moving average (NARMA) controller and fuzzy-based PID controller. The proposed PID-based NARMA controller shows better control of temperature than the conventional PID controller. The fuzzy-based PID controller also shows a reasonable optimal performance.

Fractional PID Controller Applied to a Chemical Plant with Level and pH Control

2018 ◽  
Vol 13 (4) ◽  
Author(s):  
Renato Aparecido Aguiar ◽  
Ivan Carlos Franco ◽  
Fabrizio Leonardi ◽  
Fábio Lima
Keyword(s):  
Fractional Order ◽  
Pid Control ◽  
Pid Controller ◽  
Ph Control ◽  
Dynamic Responses ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Control Effort ◽  
Multivariable Process ◽  
Fractional Order Pid

Abstract One of the most important processes in the chemical, biological and petrochemical industries is the control of the potential of hydrogen (pH). As it is a multivariable process and non-linear, pH control gives rise to many challenges for designers in both dynamic responses and robustness issues. Despite all this complexity, in many circumstances pH control is performed by using a conventional proportional integral derivative (PID) control, which is very common in industry. This paper proposes using a fractional-order PID to improve the pH control performance of a lab-scale process, as it is more flexible, i. e., there is a higher number of variables to be adjusted. Results from a simulation have been compared to those from both conventional and fractional-order PID controls, which has shown the better performance of the latter related to important metrics such as the control effort and dynamic response of the controlled variables.

Water Temperature Control Using PID Control System Based on LabVIEW

2016 ◽  
Vol 4 (2) ◽  
pp. 35-46
Author(s):  
Ari Ramadhani
Keyword(s):  
Water Temperature ◽  
Pid Control ◽  
Temperature Sensor ◽  
Pid Controller ◽  
Current Flow ◽  
Electrical Energy ◽  
Heating Process ◽  
Water Heater ◽  
Digital Thermometer ◽  
Flow Through

Abstract - Automatic system have grown widespread across all sector so do water heater. Traditionally, heating water is done by utilizing fire as heat source. As the growing of technology, the heating process could be done by manipulating electrical energy by convert it to heat. Electrical energy is flown to a metal rod that contact directly with the water which increase the water temperature. On some case, appropiate water temperature is needed. Altough, a thermometer is needed to read the actual temperature as a feedback value for the system and a system that can control the electricity current flow through the heater that the heat produced is linear to the current flow. With implementing microcontroller as a process node for generating PWM signal, this problem can be solved. Also, Labview is needed as an interface for monitoring and bursting an output which have been processed by Proportional, Integral, and Devivative (PID) controller to producing accurate and stable heat. Based on the results of testing, the system is able to provide a rapid response to any changes that occur, both changes in set-point and changes in water temperature (actual value). Another test is done by comparing the temperature value detected by the temperature sensor in this device with an external digital thermometer placed in the same place, and from some of the tests the temperature value detected by the temperature sensor in this device has a difference of ± 0.19 ℃ with a digital thermometer. Keyword : Water Heater, Thermometer, Microcontroller, LabView, PID.

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