Design of robust PI control systems based on sensitivity analysis and genetic algorithms

Abstract

Sensitivity analysis and a genetic algorithm are used in the proportional–integral controller design. A systematic procedure is proposed to improve the results of the proportional–integral controller sensitivity analyses reported in the literature, and this procedure ensures a certain gain margin and phase margin in the proportional–integral control systems. The stability boundary of the proportional–integral control systems in a parameter space is obtained by the Tan method. The genetic algorithm is also used to meet the specifications of the integral absolute error, integral time-weighted absolute error, integral square error and integral time-weighted square error. Therefore, the genetic locus can be obtained in a parameter space. The method is also used to design a proportional–integral controller for Kharitonov plants and for process control, including time delay. Computer simulations show the effectiveness of the proposed method in this article. The proposed method is also applied in a robot function, an uncertain coefficient system of position control for a motor system and a boiler steam drum process control system.