Application of Intensified Current Search to Multiobjective PID Controller Optimization

The intelligent control system design has been changed from the conventional approach to the optimization framework solved by efficient metaheuristics. The intensified current search (ICS) has been recently proposed as one of the most powerful metaheuristics for solving optimization problems. The ICS, the latest modified version of the conventional current search (CS), possesses the memory list (ML) regarded as the exploration strategy and the adaptive radius (AR) and adaptive neighborhood (AN) mechanis ms regarded as the exp loitation strategy. The ML is used to escape from local entrapment caused by any local solution, while both AR and AN mechanisms are conducted to speed up the search process. In this paper, the application of the ICS to multiobject ive PID controller design optimization for the three-phase induction motor (3-IM) speed control system is proposed. Algorithms of the ICS and its performance evaluation against multiobject ive functions are presented. As simulation results, the ICS can provide very satisfactory solutions for all test functions and the 3-IM control application. Moreover, the simulation results of motor control application are confirmed by the experimental results based on dSPACE technology.