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W.-D. Chang, “Nonlinear CSTR control system design using an artificial bee colony algorithm,” Simulation Modelling Practice and Theory, vol. 31, pp. 1-9, 2013.

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Article

Design of Nonlinear CSTR Control System using Active Disturbance Rejection Control Optimized by Asexual Reproduction Optimization

1Department of Instrumentation and Automation Engineering, Petroleum University of Technology, Ahwaz, Iran

2Department of Chemical Engineering, Petroleum University of Technology, Ahwaz, Iran

3Senior expert in Instrumentation Unit, Sarkhoon&Qeshm Gas treating Company, Bandar Abbas, Iran


Journal of Automation and Control. 2015, Vol. 3 No. 2, 36-42
DOI: 10.12691/automation-3-2-1
Copyright © 2015 Science and Education Publishing

Cite this paper:
Navid Yazdanparast, Mehdi Shahbazian, Masoud Aghajani, Saeed Pour Abed. Design of Nonlinear CSTR Control System using Active Disturbance Rejection Control Optimized by Asexual Reproduction Optimization. Journal of Automation and Control. 2015; 3(2):36-42. doi: 10.12691/automation-3-2-1.

Correspondence to: Navid  Yazdanparast, Department of Instrumentation and Automation Engineering, Petroleum University of Technology, Ahwaz, Iran. Email: Navid.yazdan@gmail.com

Abstract

This paper proposes an optimal Active Disturbance Rejection Control (ADRC) based on using Asexual Reproduction Optimization (ARO) to control the temperature of a nonlinear CSTR. The parameters of non-isothermal continuous stirred tank reactor (CSTR) are varying with time caused by fouling and the deactivation and regeneration of the catalyst. Furthermore, in the exothermal region, dynamic behavior of this reactor is unstable. Therefore, designing an efficient controller in this complicated situation is difficult and challenging. ADRC is used as a robust method to control the temperature of CSTR in the situation that the CSTR parameters are varying with time. The parameters of ADRC are difficult to adjust and if these parameters tuned properly, it performs more efficiently in setpoint tracking and disturbance rejection. In this paper Controller design is represented as an optimization problem. The parameters of ADRC are tuned by ARO and then by Particle Swarm Optimization (PSO). The performance of ADRC tuned by ARO (ADRC-ARO) is compared with the performance of ADRC tuned by PSO (ADRC-PSO) and PID controller. The simulation results that the proposed ADRC-ARO method reveals robustness and better performance in both setpoint tracking and disturbance rejection with faster response time and less settling time.

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