Differential Evolution Algorithm for System Identification and Tuning of a Fuzzy Modified Model Reference Adaptive Controller for a Coupled Tank Level Process

Abstract— Improving the transient performance of the MRAC has been a point of research for a long time. The main objective of the paper is to design an MRAC with improved transient and steady state performance. This paper proposes a Fuzzy modified MRAC (FMRAC) to control a coupled tank level process. The FMRAC uses a proportional control based Mamdani-type Fuzzy inference system (MFIS) to improve the transient performance of a direct MRAC. In addition, it proposes the application of Differential Evolution (DE) algorithm to tune the membership function parameters off-line of the FMRAC to improve its performance further. The proposed controller is called DE based Fuzzy Modified Model Reference Adaptive Controller (DEFMRAC). In this study, an MRAC, an FMRAC and the proposed DEFMRAC are designed for a coupled tank level process and their performances are compared. The coupled tank level process is modeled by using system identification procedure and the accuracy of the resultant model is further improved by parameter tuning using DE. The simulation results show that the FMRAC gives better transient performance than the direct MRAC. The results also show that the proposed DEFMRAC gives better transient performance than the direct MRAC or the FMRAC. It is concluded that the proposed controller can be used to obtain very good transient and steady state performance in the control of nonlinear processes. KeywordsModel Reference Adaptive Controller; Coupled tank process; System identification; Fuzzy modified Model Reference Adaptive Controller; Differential Evolution Algorithm; Differential Evolution based Fuzzy modified Model Reference Adaptive Controller