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Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
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Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
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Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling

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Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling
Journal Article

Robust MPC for polytopic uncertain systems via a high-rate network with the round-robin scheduling

2023
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Overview
This article is concerned with the robust model predictive control (RMPC) problem for polytopic uncertain systems under the round-robin (RR) scheduling in the high-rate communication channel. From a set of sensors to the controller, several sensors transmit the data to the remote controller via a shared high-rate communication network, data collision might happen if these sensors start transmissions at the same time. For the sake of preventing data collision in the high-rate communication channel, a communication scheduling known as RR is used to arrange the data transmission order, where only one node with token is allowed to send data at each transmission instant. In accordance with the token-dependent Lyapunov-like approach, the aim of the problem addressed is to design a set of controllers in the framework of RMPC such that the asymptotical stability of the closed-loop system is guaranteed. By taking the effect of the underlying RR scheduling in the high-rate communication channel into consideration, sufficient conditions are obtained by solving a terminal constraint set of an auxiliary optimization problem. In addition, an algorithm including both off-line and online parts is provided to find a sub-optimal solution. Finally, two simulation examples are used to demonstrate the usefulness and effectiveness of the proposed RMPC strategy.