earticle

영어

A new type controller, recurrent fuzzy neural networks-fuzzy-sliding mode controller (FRNN-FSMC), is developed for a class of large-scale systems with unknown bounds of high-order interconnections and disturbances. The main purpose is to eliminate the chattering phenomenon and to overcome the problem of the equivalent control computation. The FRNN-FSMC, which incorporates the recurrent fuzzy neural network (RFNN), fuzzy logic controller (FLC) and the SMC, can eliminate chattering using a fixed boundary layer around the switch surface. Within the boundary layer, where the FLC is applied, the chattering phenomenon, which is inherent in a SMC, is avoided by smoothing the switch signal. Moreover, to compute the equivalent controller, a feed-forward RFNN is used. The stability of the whole system is analyzed via the Lyapunov methodology. In this study, we propose an effective method to select some key controller parameters in an optimal manner by using the genetic algorithm (GA), so that a high performance of the overall system's response can be achieved. The effectiveness and efficiency of the proposed controller and optimization method were tested using highly interconnected nonlinear systems as examples.