Fuzzy adaptive linearizing control for non-affine systems

The aim of this paper is to examine the feedback linearization technique for unknown non affine-in-control systems. As the nonlinear plant is assumed to be unknown, an adaptive Takagi-Sugeno fuzzy system is used to represent it. Based on the error between the nonlinear plant and the adapted fuzzy model, the parameters of the latter are updated according to Lyapunov synthesis. Then, at each sampling time, the linearizing controller is obtained by inversion of the fuzzy model. The closed-loop control structure stability is guaranteed using Lyapunov analysis. An illustrative simulation example is given to demonstrate the feasibility of the proposed method.