PID Control for Mimo Nonlinear Processes

Abstract: This paper proposes a new type of PID controller. The desired multi input- multi-output (MIMO) nonlinear system behavior is described by a set of Takagi-Sugeno (T-S) model. However, due to the complexity of the real processes, obtaining a high quality control with a short settle time, a periodical step response and zero steady-state error is often a difficult task. Indeed, PID attempts to minimize the error between the output and the desired output. Then, the PID is insufficient to adapt to changes in system dynamics which have characteristics of complex constraints. In addition, it is shown that the PSO algorithm is sensitive to random initialization and may affect the quality of obtaining PID controller. In order to overcome these problems, chaos particle swarm optimization (CPSO) is used to perform PID controller for nonlinear MIMO process. The practicality and effectiveness of the identification and control scheme is demonstrated by simulation results involving simulations of a continuous stirred-tank reactor. Key words: Takagi-Sugeno fuzzy model PID controller MIMO Chaos particle swarm optimization Fuzzy c-means INTRODUCTION measured process variable and a desired set point. Various control methods have been utilized in various tuning schemes have been reported by many industries, one of them being the PID. This latter, researchers. S. Baskar. [13] proposed a novel covarianc