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This article investigates the predictive control scheme and related stability issue for a class of discrete-time perturbed nonlinear system with state and input constraints. First, we propose a novel control framework, i.e., networked dual-mode adaptive horizon model predictive control (MPC), which consists of a local controller, a remote controller that is subject to packet losses, and a judger coordinating the switchings between them. The optimization procedure of MPC with variable prediction horizon is implemented in the remote controller while a simple state-feedback control law is in the local one. Second, to establish the stability condition, we propose a new Lyapunov function. By specifying the relation between the Lyapunov function and the optimal MPC value function, the input-to-state practical stability is established. Finally, simulation results show the effectiveness of our proposed control scheme. [ABSTRACT FROM AUTHOR]

The input-to-state stability problem of a class of nonlinear switched networked control systems subject to time-varying transmission intervals, periodical packet dropouts, and communication constraints is investigated. By adopting the extended input-to-state stability(eISS) protocol and constructing a novel Lyapunov function, the input-to-state stability properties of such systems are discussed. Then, by making use of the small-gain theorem, the maximum allowable transmission interval to guarantee system stability is obtained. A batch reactor is finally considered to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]