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Key Words:NEURAL TRACKING CONTROL; H-INFINITY CONTROL; GLOBAL STABILIZATION; LYAPUNOV FUNCTIONS; FUZZY CONTROL; FORM; STABILITY
Abstract:In this article, adaptive tracking control for a class of switched stochastic nonlinear systems subject to unknown dead-zone input using multi-dimensional Taylor network (MTN) is studied. Firstly, the characteristic function is introduced to convert the nonlinearity of the input dead-zone into a linear model. Secondly, a novel adaptive control method based on the backstepping recursive design technique is proposed, which combines MTN and common Lyapunov functions (CLFs). Significantly, a method to reduce the computational complexity of switched stochastic nonlinear systems is proposed for the first time, which introduces characteristic function and MTN technology. The result makes clear that the proposed controller can ensure all signals of the closed-loop system are bounded in probability, and the output of the system can track reference signal well. Finally, the effectiveness of proposed control method is verified by simulation results.
Volume:21
Issue:2
Translation or Not:no