基于LQR方法的高阶异构线性多智能体系统逆向优化一致性

Arian Yousefiankalareh, Ehsan Salajegheh, Farzad Shahabi, Hossein Mirzanejad, Shahab Balali, Shahaboddin Seddighi
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引用次数: 1

摘要

本文利用基于LQR的最优控制理论,对保证线性智能体输出一致性的合作控制律进行优化。首先,我们研究了高阶异构线性网络的一致性问题。然后给出闭环合作系统共识的局部优化问题的解析解。多智能体系统的最优控制具有一定的复杂性。由于网络的动态性取决于网络图的拓扑结构,而网络拓扑结构必须存在于最优解中,因此我们采用逆向优化方法。解析解结果表明,逆向优化能成功地得到一致的结果。
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Reverse Optimizing Consensus of Higher-Order Heterogeneous Linear Multiagent Systems Based on LQR method
This paper utilizes an optimum control theory based on LQR to optimize a cooperative control law that ensures the consensus of linear agents’ outputs. In the beginning, we study the consensus problem of higher-order heterogeneous linear networks. Then we will provide an analytic solution for the partial optimization problem of closed-loop cooperative systems consensus. Optimum control of multiagent systems has some complications. Since network dynamic depends on network graph topology and network topology should exist in optimum solution, we utilize the reverse optimization method. The analytic solution outcome demonstrated that the reverse optimization would successfully result in consensus.
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