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Adaptive Event-Triggered Robust Model Predictive Control for Multiagent Systems With Time-Varying Delay Under Arbitrary Network Topology
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DOI：10.1109/JSYST.2023.3313232.png)
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Abstract
En 中文
In this article, the consensus problem is investigated for discrete-time linear multiagent systems (MASs) under arbitrary network topology, where each agent is subject to time-varying delays, input constraints, and external disturbances as well, and an adaptive event-triggered robust model predictive control (RMPC) scheme is proposed. By employing a minimum number of leader-nodes algorithm, and introducing a virtual leader to link with the allocated leader-nodes, the arbitrary network topology is reconstructed into a network topology that includes a directed spanning tree, so that a leader-following consensus problem under directed topology is established. An event-triggered RMPC protocol is then developed to address the consensus control of the MASs, in which a novel adaptive event-triggered mechanism is used to save the computation and communication resources. It can be proven that the asymptotic stability with H-infinity performance can be guaranteed, and the sufficient conditions can be given in terms of linear matrix inequalities (LMIs). The controller gain can be obtained by solving a constrained optimization problem subject to LMIs, and the matrix dimension will not increase with the number of the agents. Finally, simulation results are given to illustrate the effectiveness of the proposed method.
Keywords:
Adaptive event-triggered scheme
arbitrary network topology
input constraint
multiagent systems (MASs)
robust model predictive control (RMPC)
time-varying delay
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