Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach
This paper presents a distributed optimal model reference adaptive control approach for solving containment control of heterogeneous multi-agent systems (MASs) with non-autonomous leaders. First, a fully distributed adaptive observer is designed to provide for each agent the desired reference trajec...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8501968/ |
| _version_ | 1819162982815367168 |
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| author | Yongliang Yang Shusen Cheng Yixin Yin Donald C. Wunsch |
| author_facet | Yongliang Yang Shusen Cheng Yixin Yin Donald C. Wunsch |
| author_sort | Yongliang Yang |
| collection | DOAJ |
| description | This paper presents a distributed optimal model reference adaptive control approach for solving containment control of heterogeneous multi-agent systems (MASs) with non-autonomous leaders. First, a fully distributed adaptive observer is designed to provide for each agent the desired reference trajectory by estimating the convex hull spanned by leaders. The distributed observer dynamics serves as a reference model for each follower to synchronize. The global communication graph information or the leader dynamics is not required to design the observer. In contrast to existing model reference adaptive controllers (MRAC) for single-agent systems and containment control solutions for MASs, the proposed MRAC approach imposes optimality and presents a distributed adaptive optimal solution to the containment control problem. To impose optimality, a performance function is defined based on the adaptive observers' states as well as the followers' local measurements. It is shown that considering non-autonomous leaders in this optimal control problem leads to solving inhomogeneous algebraic Riccati equations (AREs), instead of normal AREs in standard optimal control problems. To obviate the requirement of knowing the agents' dynamics, an off-policy reinforcement learning approach implemented on an actor-critic structure is utilized for solving the inhomogeneous ARE. A simulation example is conducted to illustrate the effectiveness of the presented method. |
| first_indexed | 2024-12-22T17:36:54Z |
| format | Article |
| id | doaj.art-9f0786f8ce284659a123b73ffcb5cc3e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T17:36:54Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-9f0786f8ce284659a123b73ffcb5cc3e2022-12-21T18:18:30ZengIEEEIEEE Access2169-35362018-01-016606896070310.1109/ACCESS.2018.28760418501968Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference ApproachYongliang Yang0https://orcid.org/0000-0002-3144-8604Shusen Cheng1Yixin Yin2Donald C. Wunsch3https://orcid.org/0000-0002-9726-9051School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, ChinaSchool of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing, ChinaSchool of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing, ChinaDepartment of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO, USAThis paper presents a distributed optimal model reference adaptive control approach for solving containment control of heterogeneous multi-agent systems (MASs) with non-autonomous leaders. First, a fully distributed adaptive observer is designed to provide for each agent the desired reference trajectory by estimating the convex hull spanned by leaders. The distributed observer dynamics serves as a reference model for each follower to synchronize. The global communication graph information or the leader dynamics is not required to design the observer. In contrast to existing model reference adaptive controllers (MRAC) for single-agent systems and containment control solutions for MASs, the proposed MRAC approach imposes optimality and presents a distributed adaptive optimal solution to the containment control problem. To impose optimality, a performance function is defined based on the adaptive observers' states as well as the followers' local measurements. It is shown that considering non-autonomous leaders in this optimal control problem leads to solving inhomogeneous algebraic Riccati equations (AREs), instead of normal AREs in standard optimal control problems. To obviate the requirement of knowing the agents' dynamics, an off-policy reinforcement learning approach implemented on an actor-critic structure is utilized for solving the inhomogeneous ARE. A simulation example is conducted to illustrate the effectiveness of the presented method.https://ieeexplore.ieee.org/document/8501968/Containment controlheterogeneous multi-agent systemsnon-autonomous leaderfully distributed observeroptimal model reference approachmodel-free reinforcement learning |
| spellingShingle | Yongliang Yang Shusen Cheng Yixin Yin Donald C. Wunsch Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach IEEE Access Containment control heterogeneous multi-agent systems non-autonomous leader fully distributed observer optimal model reference approach model-free reinforcement learning |
| title | Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach |
| title_full | Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach |
| title_fullStr | Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach |
| title_full_unstemmed | Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach |
| title_short | Containment Control of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach |
| title_sort | containment control of heterogeneous systems with non autonomous leaders a distributed optimal model reference approach |
| topic | Containment control heterogeneous multi-agent systems non-autonomous leader fully distributed observer optimal model reference approach model-free reinforcement learning |
| url | https://ieeexplore.ieee.org/document/8501968/ |
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