Optimal Fuzzy Switching Grey Prediction with RGA for TRMS Control

Abstract

This paper presents a fuzzy switching grey prediction PID controller to an experimental propeller setup which is called the twin rotor multi-input multi-output system (TRMS). The goal of this study is to stabilize the TRMS in significant cross coupling conditions and to experiment with set-point control and trajectory tracking. The proposed scheme enhances the grey prediction method of difference equations, which is a single variable second order grey model (DGM(2,1) model). It is performed by a real-valued genetic algorithm (RGA) with a system performance index as fitness function. We apply the integral of time multiplied by the square error criterion (ITSE) to form a suitable fitness function in RGA. Simulation results show that the proposed design can successfully adapt to system nonlinearity and complex coupling conditions. Computer simulations show that the proposed approach has better performance than pervious works.