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In this paper, adaptive variable structure neural control is investigated for a class of nonlinear systems under the effects of time-varying state delays and uncertain hysteresis inputs. The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design, and the effect of the uncertain hysteresis with the Prandtl-Ishlinskii (PI) model representation...
The notions of the practical stability in probability and in the pth mean, and the practical controllability in probability and in the pth mean, are introduced for some stochastic systems with Markovian jump parameters and time-varying delays. Sufficient conditions on such practical properties are obtained by using the comparison principle and the Lyapunov function methods. Besides, for a class of...
A new method is proposed to design delay-dependent stability controller for nonlinear systems with time-varying delay in this paper. It is presented by introducing a new type of Lyapunov function. Different from the general processing method, no any term is ignored during the process of analyzing. The controller is obtained by considering the additional useful terms, which were ignored in previous...
This paper researches the robust control stabilization problem of a continuous nonlinear system with time-invarying delays in the state vector. A sufficient condition of the system stabilization is achieved through radial basis neural network (RBF) approximating unknown function, and an adaptive neural controller of time-delay independent is obtained. A good result is got for the stabilization control...
In this paper, stabilization control problem for a class of two dimensional Markovian jumping nonlinear systems with time-delays is investigated. A sufficient condition of existence and uniqueness of the solution process to Markovian jumping nonlinear systems is given. And, a criterion for asymptotical stability in probability is obtained. Through properly constructing Lyapunov function and using...
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