Modified PSO for Optimal Tuning of Fuzzy PID Controller

Fuzzy PID controllers provide a promising approach for industrial applications with many desirable features. However, the large number of parameters and rule bases make self-tuning fuzzy PID controller optimization a complex task. In this paper, a novel tuning method based on the development of the standard particle swarm optimization (PSO) is proposed for optimum design of fuzzy PID controller for multivariable system. The parameters of membership functions and PID gains are optimized using modified PSO which is an efficient and simple tool for multidimensional problem. Based on the structure of the modified PSO, each particle in swarm population is divided into number of parts according to the number of inputs-outputs system, which means that each part of particle represents one input-output system controller. The new development in PSO for multi inputs-outputs system is based on tuning all the parts of each particle in swarm population in parallel. The system performance is enhanced by minimizing the error function between all inputs-outputs controller represented by the different parts of particle simultaneously instead of minimizing sum of error of whole inputs-outputs system controllers. The parameters of fuzzy controller and the PID gains are tuned simultaneously. Besides, a design methodology is introduced to combine the classical PID and fuzzy logic controller. The hybrid PID, FLC, and PSO is applied to an aerobic unit in wastewater treatment process for further improvements in steady state error and high system performance. The obtained results show that, the response of the biological system in both transient and steady state has improved significantly compared to both fuzzy PID and fuzzy PID tuned by the standard PSO.