Adaptive Non‐Backstepping Fuzzy Control for a Class of Uncertain Nonlinear Systems with Unknown Dead‐Zone Input

Based on the approximation property of fuzzy logic systems, we propose a novel non-backstepping adaptive tracking control algorithm for a class of single input single output (SISO) strict-feedback nonlinear systems with unknown dead-zone input. In this algorithm, we introduce some novel state variables and coordinate transforms to convert the strict-feedback form into a normal one, and it is not necessary to consider the traditional approximation-based the backstepping scheme. Due to new states variables being unavailable, the tracking control is changed from a state-feedback one to an output-feedback one. So, observers need to be designed to estimate the indirect nonmeasurable states. According to Lyapunov stability analysis method, the developed controller can guarantee that all of the signals in the closed-loop system will be ultimately uniformly bounded (UUB), and the output can track the reference signal very well. Simulation results are presented to show the effectiveness of the proposed approach.

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