Title: Tuning optimal PID controller

Authors: Adel Taeib; Abdelkader Chaari

Addresses: Department of Electrical Engineering, National High School of Engineers of Tunis (ENSIT), Tunis, Tunisia ' Department of Electrical Engineering, National High School of Engineers of Tunis (ENSIT), Tunis, Tunisia

Abstract: In this paper, a novel design method for determining the optimal proportional-integral-derivative (PID) controller parameters for nonlinear multiple-input multiple-output (MIMO) system using the particle swarm optimisation (PSO) algorithm is presented. Firstly, a nonlinear system was described based on Takagi-Sugeno (T-S) fuzzy models. Assuming that the antecedent parameters of T-S models were kept, the consequent parameters were identified online by using the weighted recursive least square (WRLS) method. Secondly, the identified parameters of fuzzy model were used to directly receive the model predicted output with direct iterative for the T-S model. The fast tuning of optimum PID controller parameters yields high-quality solution. In order to assist estimating the performance of the proposed PSO-PID controller, a new time-domain performance criterion function was also defined. Finally, the application results for continuous stirred tank reactor (CSTR) process show that the proposed algorithm is an effective control strategy with excellent tracing ability.

Keywords: fuzzy modelling; Takagi-Sugeno models; proportional-integral-derivative; PID control; particle swarm optimisation; PSO; controller tuning; optimal control; nonlinear systems; MIMO systems; continuous stirred tank reactors; CSTR process; tracing ability.

DOI: 10.1504/IJMIC.2015.068872

International Journal of Modelling, Identification and Control, 2015 Vol.23 No.2, pp.140 - 147

Received: 20 Jan 2014
Accepted: 17 Sep 2014
Published online: 16 Apr 2015 *

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