Design of Differential Evolution Optimized PI Controller for a Temperature Process

Abstract

Differential evolution is a new stochastic population-based optimization algorithm. It is an accurate, fast and robust optimization method. In this paper, a PI controller is used and differential evolution optimization technique is used to optimize the controller parameters. The robust controller parameters are obtained by solving the optimization problem, which consists of objective functions and constraints, using differential evolution method. Here differential evolution is implemented in tuning of a PI controller for a temperature process. The performance of the optimized PI controller is compared with that of the Zeigler-Nichols method and the simulation results show the improved performance of the optimized controller.

Keywords: Evolutionary algorithm (EA), differential evolution (DE), PID controller tuning, Zeigler-Nichols (Z-N), initial steady state (ISS), temperature process, optimization