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For a class of uncertain time-delay nonlinear systems represented by Takagi-Sugeno fuzzy models, the finite-time stabilization problem with exogenous disturbances is discussed. Based on the stochastic Lyapunov-Krasovskii functional approach, a new finite-time stabilization condition is established for such fuzzy systems. By applying linear matrix inequality technique, the finite-time state feedback...
In this paper, a robust fuzzy model predictive control (MPC) scheme is presented for a class of discrete-time nonlinear systems which can be described by uncertain T-S fuzzy models subject to actuator saturation. The system uncertainties under consideration are assumed to be time-varying and norm-bounded. A sufficient condition of minimizing upper bound of the cost function and asymptotical stability...
A robust receding horizon dual-mode control method is proposed for a class of uncertain discrete-time nonlinear systems using Takagi-Sugeno fuzzy models subject to input and state constraints. The uncertainties are considered to exist in system parameters and assumed to belong to a polytopic set. Using the property of the invariant ellipsoid, a receding horizon dual-mode control that satisfies the...
The problems of stochastic stability and sliding mode Hinfin control for a class of nonlinear matched and mismatched uncertain systems with stochastic jumps are considered in this paper. The uncertain system under consideration may have mismatched norm bounded uncertainties in the state matrix. The transition of the jumping parameters in the systems is governed by a finite-state Markov process. A...
This paper is concerned with the problem of robust Hinfin control for a class of uncertain nonlinear Markovian jump systems described by the Takagi-Sugeno (T-S) fuzzy models. The aim is to find a mode-dependent state feedback controller such that the closed-loop fuzzy jump system is robustly stochastically stable and a prescribed Hinfin performance level is satisfied for all admissible uncertainties...
A full-order robust Hinfin filtering design for a class of uncertain nonlinear systems was investigated. The nonlinearities are modeled by neural-networks and then represented by linear difference inclusions. The uncertainties are described by polytope type. The presented filter is linear time-invariant, which not only guarantees the robust stability of error system but also satisfies a prescribed...
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