Learning-based Fuzzy Control for Strict-feedback Nonlinear Systems with Unknown Uncertainties

The fuzzy control problem for a sort of uncertain strict-feedback nonlinear systems is examined in this article. Fuzzy logic systems (FLSs) approximate the unknown uncertainties of considered systems, whose fast convergence is guaranteed by novel gradient-descent based parameter updating laws. The closed-loop system is shown to be semi-globally uniformly ultimately bounded (SUUB) by Lyapunov function-based approach. To demonstrate the efficacy of the presented scheme, a simulation example on inverted pendulum is provided along with some comparison results.