Fuzzy Linearizing Control Approach for a Class of Nonlinear Discrete-Time Systems and its Equivalence with Internal Model Control Structure

This paper examines the control problem of discrete-time feedback linearizable nonlinear systems for which there is no available analytic models. Based on the ability of fuzzy systems to approximate any nonlinear mapping, the unknown nonlinear system is represented by a Takagi-Sugeno fuzzy model which is identified using input-output data. Then, a fuzzy feedback linearizing controller, based on fuzzy model inversion, is used to linearize the system. The key concept is the combination of this fuzzy feedback linearizing controller with a simple linear controller resulting in a robust feedback control structure. The equivalence between the feedback linearization technique and the internal model control methodology is then established. Finally, simulation results are given to demonstrate the feasibility of the proposed method.