Adaptive fuzzy control for pure-feedback stochastic nonlinear systems with unknown dead-zone input

Huanqing Wang, Bing Chen and Chong Lin

International Journal of Systems Science, 2014, vol. 45, issue 12, 2552-2564

Abstract: This paper is concerned with the problem of adaptive fuzzy output tracking control for a class of nonlinear pure-feedback stochastic systems with unknown dead-zone. Fuzzy logic systems in Mamdani type are used to approximate the unknown nonlinearities, then a novel adaptive fuzzy tracking controller is designed by using backstepping technique. The control scheme is systematically derived without requiring any information on the boundedness of dead-zone parameters (slopes and break-points) and the repeated differentiation of the virtual control signals. The proposed adaptive fuzzy controller guarantees that all the signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighbourhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

Date: 2014
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DOI: 10.1080/00207721.2013.773470

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