基于迭代学习的具适多智能体系统分布式跟踪控制
文章考虑了具适多智能体系统的分布式跟踪控制问题.通过设计带有初始学习机制的P型和PD.型迭代学习控制策略求解跟踪问题.具适导数具有良好的性质且可以刻画不同步长的实际数据采样情况.初始学习机制放松了初始值条件且提高了算法实现趋同跟踪的性能.在可重复操作环境和有向通信拓扑的假设下,提出了一种分布式迭代学习方案,通过重复同一轨迹的控制尝试和用跟踪误差修正不满意的控制信号来实现有限时间趋同.严格证明了随着迭代次数增加,提出的P型和PDα型迭代学习控制策略使得所有智能体能渐近跟踪上参考轨迹.两个代表性数值仿真验证了算法的有效性....
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| Published in | 控制理论与应用 Vol. 39; no. 10; pp. 1836 - 1844 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
山东大学控制科学与工程学院,山东济南250061%贵州大学数学与统计学院,贵州贵阳550025
01.10.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-8152 |
| DOI | 10.7641/CTA.2022.10937 |
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| Abstract | 文章考虑了具适多智能体系统的分布式跟踪控制问题.通过设计带有初始学习机制的P型和PD.型迭代学习控制策略求解跟踪问题.具适导数具有良好的性质且可以刻画不同步长的实际数据采样情况.初始学习机制放松了初始值条件且提高了算法实现趋同跟踪的性能.在可重复操作环境和有向通信拓扑的假设下,提出了一种分布式迭代学习方案,通过重复同一轨迹的控制尝试和用跟踪误差修正不满意的控制信号来实现有限时间趋同.严格证明了随着迭代次数增加,提出的P型和PDα型迭代学习控制策略使得所有智能体能渐近跟踪上参考轨迹.两个代表性数值仿真验证了算法的有效性. |
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| AbstractList | 文章考虑了具适多智能体系统的分布式跟踪控制问题.通过设计带有初始学习机制的P型和PD.型迭代学习控制策略求解跟踪问题.具适导数具有良好的性质且可以刻画不同步长的实际数据采样情况.初始学习机制放松了初始值条件且提高了算法实现趋同跟踪的性能.在可重复操作环境和有向通信拓扑的假设下,提出了一种分布式迭代学习方案,通过重复同一轨迹的控制尝试和用跟踪误差修正不满意的控制信号来实现有限时间趋同.严格证明了随着迭代次数增加,提出的P型和PDα型迭代学习控制策略使得所有智能体能渐近跟踪上参考轨迹.两个代表性数值仿真验证了算法的有效性. |
| Abstract_FL | This paper considers the consensus tracking control problem for conformable multi-agent systems with linear and nonlinear dynamics by designing P-type and PDα-type iterative learning control law with initial learning mechanisms.Conformable derivative is well-behaved and can characterize a different step in real data sampling.The initial learning mechanism relaxes the initial value condition and improves the performance of the protocol to achieve consensus tracking.A distributed iterative learning scheme is proposed to realize the finite-time consensus by repeating the control attempt of the same trajectory and correcting the unsatisfactory control signal with the tracking error under the assumption of repeatable operation environments as well as a directed communication topology.The asymptotical convergence of the proposed P-type and the PDα-type distributed iterative learning protocol for all agents is strictly proved as the iteration number increases.Two numerical examples are simulated to verify the effectiveness of the protocols. |
| Author | 王锦荣 王小文 刘帅 |
| AuthorAffiliation | 山东大学控制科学与工程学院,山东济南250061%贵州大学数学与统计学院,贵州贵阳550025 |
| AuthorAffiliation_xml | – name: 山东大学控制科学与工程学院,山东济南250061%贵州大学数学与统计学院,贵州贵阳550025 |
| Author_FL | WANG Xiao-wen LIU Shuai WANG Jin-rong |
| Author_FL_xml | – sequence: 1 fullname: WANG Xiao-wen – sequence: 2 fullname: LIU Shuai – sequence: 3 fullname: WANG Jin-rong |
| Author_xml | – sequence: 1 fullname: 王小文 – sequence: 2 fullname: 刘帅 – sequence: 3 fullname: 王锦荣 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.7641/CTA.2022.10937 |
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| DocumentTitle_FL | Iterative learning-based consensus tracking control for conformable multi-agent systems |
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| Keywords | multi-agent systems 迭代技术 conformable derivative 多智能体系统 趋同跟踪控制 consensus tracking control iterative techniques 具适导数 |
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| Publisher | 山东大学控制科学与工程学院,山东济南250061%贵州大学数学与统计学院,贵州贵阳550025 |
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| Snippet | 文章考虑了具适多智能体系统的分布式跟踪控制问题.通过设计带有初始学习机制的P型和PD.型迭代学习控制策略求解跟踪问题.具适导数具有良好的性质且可以刻画不同步长的实际... |
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| Title | 基于迭代学习的具适多智能体系统分布式跟踪控制 |
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