title: Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints.
abstract: This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.
authors.forename: Huanqing
authors.initials: H
authors.lastname: Wang
authors.forename: Bing
authors.initials: B
authors.lastname: Chen
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Liu
authors.forename: Kefu
authors.initials: K
authors.lastname: Liu
authors.forename: Chong
authors.initials: C
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003661:Decision Support Techniques; D005246:Feedback; D017143:Fuzzy Logic; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D013269:Stochastic Processes