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A Fuzzy Neural Network based Adaptive Terminal Iterative Learning Control for Nonaffine Nonlinear Discrete-Time Systems

关键字:Data-driven control; Model-free adaptive control; Switching Control; Nonlinear system; Unknown control direction

摘要:In this paper, a model-free adaptive switching control (MFASC) approach is proposed for a class of discrete-time nonlinear systems with unknown control direction. The control scheme consists of a control algorithm, a parameter estimation algorithm and a switching mechanism. Its distinct feature is that the controller design depends merely on the measured input and output data of the controlled plant without requiring any other modeling information of the plant, and it is able to deal with the system with unknown control direction by introducing a hysteresis switching mechanism. Numerical simulations show the effectiveness of the proposed approach.

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