Fuzzy Neural Network Adaptive Robust Control of a Class of Nonlinear Interconnected System Based on T-S Fuzzy Model

【摘要】：正In this paper,a fuzzy neural network control scheme is developed for a class of nonlinear interconnected system.The robust adaptive controller is designed based on the T-S fuzzy model of the original system,which includes three parts:constant state feedback gains matrix for T-S fuzzy model,neural network to approximate the interconnections and an approximation error compensator,which attenuates the effect of neural network approximation error.In this new control scheme,it is not needed to find a common positive definite matrix satisfying Riccati matrix inequality,and neither constraint nor matching conditions is required.The controller not only ensures the stability of closed-loop system,but also realizes the tracking performance objective.The emulation illustrates the validation of the designed scheme.