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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
Hossein Baloochian
Gonabad Branch, Islamic Azad University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Multi Objective Optimization of Multi Component Isothermal Liquid-Phase Kinetic Sequence using Multivariable PI Control Samira Zamiri; Saeed Balochian; Hossein Baloochian
Bulletin of Electrical Engineering and Informatics Vol 3, No 4: December 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (101.946 KB) | DOI: 10.11591/eei.v3i4.293

Abstract

In this paper, an optimal tuned saturated PI type controller with anti-windup structure is used for process control. In first step, a single objective genetic algorithm is used to find the optimal values of controller parameters. To show the difference between optimal and non-optimal control, we use this controller to track the square pulse. The results show that by choosing the control parameters randomly the output cannot track the reference signal but by optimizing the control parameters, the error, and settling time decreases significantly and efficiency of control increases but it needs more control effort. To find the optimal control parameters with lower control input, a multi objective genetic algorithm is used in next step and three points in Pareto front are analysed. It is shown that this method increases the control efficiency and needs lower control input than obtained by single objective genetic algorithm.
Multi Objective Optimization of Multi Component Isothermal Liquid-Phase Kinetic Sequence using Multivariable PI Control Samira Zamiri; Saeed Balochian; Hossein Baloochian
Bulletin of Electrical Engineering and Informatics Vol 3, No 4: December 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v3i4.293

Abstract

In this paper, an optimal tuned saturated PI type controller with anti-windup structure is used for process control. In first step, a single objective genetic algorithm is used to find the optimal values of controller parameters. To show the difference between optimal and non-optimal control, we use this controller to track the square pulse. The results show that by choosing the control parameters randomly the output cannot track the reference signal but by optimizing the control parameters, the error, and settling time decreases significantly and efficiency of control increases but it needs more control effort. To find the optimal control parameters with lower control input, a multi objective genetic algorithm is used in next step and three points in Pareto front are analysed. It is shown that this method increases the control efficiency and needs lower control input than obtained by single objective genetic algorithm.
Multi Objective Optimization of Multi Component Isothermal Liquid-Phase Kinetic Sequence using Multivariable PI Control Samira Zamiri; Saeed Balochian; Hossein Baloochian
Bulletin of Electrical Engineering and Informatics Vol 3, No 4: December 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (101.946 KB) | DOI: 10.11591/eei.v3i4.293

Abstract

In this paper, an optimal tuned saturated PI type controller with anti-windup structure is used for process control. In first step, a single objective genetic algorithm is used to find the optimal values of controller parameters. To show the difference between optimal and non-optimal control, we use this controller to track the square pulse. The results show that by choosing the control parameters randomly the output cannot track the reference signal but by optimizing the control parameters, the error, and settling time decreases significantly and efficiency of control increases but it needs more control effort. To find the optimal control parameters with lower control input, a multi objective genetic algorithm is used in next step and three points in Pareto front are analysed. It is shown that this method increases the control efficiency and needs lower control input than obtained by single objective genetic algorithm.
Co-Authors Saeed Balochian Samira Zamiri