Title :
Design Optimization of PID Controller in Automatic Voltage Regulator System Using Taguchi Combined Genetic Algorithm Method
Author :
Hasanien, Hany M.
Author_Institution :
Electr. Eng. Dept., King Saud Univ., Riyadh, Saudi Arabia
Abstract :
The optimum design of the proportional-integral-derivative (PID) controller plays an important role in achieving a satisfactory response in the automatic voltage regulator (AVR) system. This paper presents a novel optimal design of the PID controller in the AVR system by using the Taguchi combined genetic algorithm (TCGA) method. A multiobjective design optimization is introduced to minimize the maximum percentage overshoot, the rise time, the settling time, and the steady-state error of the terminal voltage of the synchronous generator. The proportional gain, the integral gain, the derivative gain, and the saturation limit define the search space for the optimization problem. The approximate optimum values of the design variables are determined by the Taguchi method using analysis of means. Analysis of variance is used to select the two most influential design variables. A multiobjective GA is used to obtain the accurate optimum values of these two variables. MATLAB toolboxes are used for this paper. The effectiveness of the proposed method is then compared with that of the earlier GA method and the particle swarm optimization method. With this proposed TCGA method, the step response of the AVR system can be improved.
Keywords :
control system synthesis; genetic algorithms; mathematics computing; particle swarm optimisation; three-term control; voltage regulators; AVR system; Matlab toolboxes; PID controller; TCGA; Taguchi combined genetic algorithm method; automatic voltage regulator system; design optimization; particle swarm optimization; proportional-integral-derivative controller; Analysis of variance; Design optimization; Genetic algorithms; MATLAB; Mathematical model; Voltage control; Automatic voltage regulator (AVR) system; Taguchi method; design optimization; genetic algorithm (GA); proportional-integral-derivative (PID) controller;
Journal_Title :
Systems Journal, IEEE
DOI :
10.1109/JSYST.2012.2219912