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This paper presents an adaptive control method for a class of nonlinear systems with matched uncertainties. Firstly, radial basis function neural networks is adopted to approximate the unknown system perturbance, then an robust adaptive control law is developed to stabilize the system based on the so-called integral sliding mode design approach. The reachability of the sliding surface and the convergence...
This paper deals with the design of a robust adaptive fuzzy tracking control for a class of uncertain and disturbed nonlinear systems. In addition to the desired performances and the convergence of the tracking error, the proposed approach guarantees the uniformly ultimately boundedness of the resulting closed-loop system. Furthermore, it allows overcoming many problems related to adaptive fuzzy controllers...
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