A data-driven α-policy iteration algorithm for optimal leader-following consensus of discrete-time multi-agent systems
In this paper, the data-driven α-policy iteration (PI) algorithm is proposed to address the optimal leader-following consensus problem of discrete-time multi-agent systems (MASs). Unlike existing results for state consensus problem that utilise the PI algorithm, the novel algorithm leverages only th...
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| Vydané v: | International journal of systems science Ročník 56; číslo 16; s. 4055 - 4072 |
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| Jazyk: | English |
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Taylor & Francis
10.12.2025
Taylor & Francis Ltd |
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| Abstract | In this paper, the data-driven α-policy iteration (PI) algorithm is proposed to address the optimal leader-following consensus problem of discrete-time multi-agent systems (MASs). Unlike existing results for state consensus problem that utilise the PI algorithm, the novel algorithm leverages only the system's trajectory from historical data over a finite number of steps and and does not require an admissible initial policy. Firstly, the linear quadratic regulator (LQR) design method is applied to derive the Bellman equation and the control policy based on the available measured data. Then, the data-driven α-PI algorithm is introduced, demonstrating a convergence rate that outperforms the value iteration (VI) algorithm and enabling all follower agents to track the trajectory of the leader agent. Finally, two examples are presented to demonstrate the performance of the proposed method. |
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| AbstractList | In this paper, the data-driven α-policy iteration (PI) algorithm is proposed to address the optimal leader-following consensus problem of discrete-time multi-agent systems (MASs). Unlike existing results for state consensus problem that utilise the PI algorithm, the novel algorithm leverages only the system's trajectory from historical data over a finite number of steps and and does not require an admissible initial policy. Firstly, the linear quadratic regulator (LQR) design method is applied to derive the Bellman equation and the control policy based on the available measured data. Then, the data-driven α-PI algorithm is introduced, demonstrating a convergence rate that outperforms the value iteration (VI) algorithm and enabling all follower agents to track the trajectory of the leader agent. Finally, two examples are presented to demonstrate the performance of the proposed method. |
| Author | Xiang, Aoxue Ma, Ruicheng Zhao, Xinyuan |
| Author_xml | – sequence: 1 givenname: Aoxue surname: Xiang fullname: Xiang, Aoxue organization: Beijing University of Technology – sequence: 2 givenname: Xinyuan surname: Zhao fullname: Zhao, Xinyuan organization: Beijing University of Technology – sequence: 3 givenname: Ruicheng surname: Ma fullname: Ma, Ruicheng email: maruicheng@lnu.edu.cn organization: Liaoning University |
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| Cites_doi | 10.1109/TNNLS.2017.2728622 10.1109/TCSII.2021.3120791 10.1109/TAC.2013.2275670 10.1109/TIE.41 10.1080/17517571003763380 10.1080/00207721.2024.2367711 10.1109/TAC.2024.3433668 10.1109/TSMC.2024.3389689 10.1109/TFUZZ.2020.3021714 10.1109/TSMC.6221021 10.1016/j.ins.2017.07.014 10.1016/j.automatica.2014.10.047 10.1109/TCSII.2021.3131360 10.1016/j.mechatronics.2005.08.002 10.1016/j.automatica.2017.07.004 10.1016/j.neucom.2022.10.032 10.1109/TASE.2024.3484412 10.3390/robotics6040022 10.1002/asjc.v25.6 10.1080/00207721.2024.2328785 10.1109/TCYB.2014.2384016 10.1109/TNNLS.2023.3303863 10.1109/TNNLS.2022.3213566 10.1109/TNNLS.2021.3098985 10.1109/TCYB.2024.3418190 10.1080/00207179.2019.1583376 10.1016/j.automatica.2023.111198 10.1109/TNNLS.2021.3122458 10.1080/00207721.2024.2410458 10.1080/00207721.2024.2371019 10.1109/TNNLS.2023.3244934 10.1109/TCYB.2023.3274908 10.1109/TII.2023.3342881 10.3390/robotics12050121 10.1109/TAC.9 10.1080/00207721.2024.2304121 |
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| SubjectTerms | Bellman theory Discrete time systems Iterative algorithms Linear quadratic regulator model-free Multi-agent systems Multiagent systems reinforcement learning state consensus α-policy iteration |
| Title | A data-driven α-policy iteration algorithm for optimal leader-following consensus of discrete-time multi-agent systems |
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