Chapter 17 - Development of a Fractional-Order PID Controller Using Adaptive Weighted PSO and Genetic Algorithms With Applications

Abstract

This chapter focuses on the application of a fractional-order PID (FOPID) controller tuned with adaptive weighted particle swarm optimization (AWPSO) and genetic algorithms (GAs) on two different models. The first application is the temperature control for continuous stirred tank reactor. The second application demonstrates a car active suspension system. The FOPID controller parameters include three parameters as a PID controller and another two parameters to furnish the FOPID structure. The parameters of the FOPID controller (the PID part) for each application have been, first, estimated and tuned using the AWPSO and the other two parameters for the FOPID controller have been, optimally, estimated using the GA. The transient behavior of the two applications has shown an acceptable behavior compared to the conventional PI/PID controllers tuned by the AWPSO only. Three different error criteria have been selected for the two applications to testify the optimum tuned parameters of the two different classes of controllers. These error criteria are the integral square error, the integral absolute error, and integral time absolute error. The results recommend the extension of the proposed FOPID controller in some other areas of engineering applications.