Adaptive Reconfigurable Control Based On T-S Fuzzy Model

The adaptive neural network controller, which based on the T-S fuzzy model, is used to design fuzzy controller. The effect of the uncertainties and the error caused by fuzzy modeling is overcome by the controller. and full adaptive reconfigurable control is used to improve the performance of fuzzy robust tracking control.This article first introduces the basic status and the developmentoverview of the self-repair reconfigurable control, then discusses the existing problems in current research areas and the prospect of development.Secondly, this paper introduced the basic knowledge and theory of fuzzy system, T-S fuzzy model, fault diagnosis, self-repairing control and neural network. A adaptive reconfigurable control method is presented based on T-S fuzzy model which contraposing the effect of the reconfigurable control caused by the modeling error, disturbance or system failure and maintain the handling qualities of the system. Based on T-S fuzzy model ,the controller can turn membership function automatically through the overall control scheme being constructed by the learning ability of neural network, and the controller can be improved the flexibility through the same way. The law of reconfigurable control can make the outputs of impaired system tracking those of reference model accurately. And it can be used to compensate non-linear dynamics caused by failure. Simulation shows that the reconfigurable method receives a good effect.Finally, based on the T-S fuzzy model, the program of adaptive reconfigurable control is used to repair the complex non-linear system. Simulation example is given to illustrate the effectiveness of the proposed method.