Lyapunov, Adaptive, and Optimal Design Techniques for Cooperative Systems on Directed Communication Graphs

Zhang, Hongwei; Lewis, Frank L.; Qu, Zhihua

doi:10.1109/tie.2011.2160140

Cited by 592 publications

(194 citation statements)

References 34 publications

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“…Besides, cooperative control of multiple AUVs with less communication is of special interest in practical implementations. In order to eliminate the need of global knowledge of the reference speed, one option is to employ the distributed control strategy [33,34] proposed a distributed observer that enables the leader to be followed in the presence of unknown reference speed. Then, a leader-follower problem for a multi-agent system under a switching topology is solved.…”

Section: Introductionmentioning

confidence: 99%

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Wang

Liu

2018

Neurocomputing

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Section: Introductionmentioning

confidence: 99%

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Wang

Liu

2018

Neurocomputing

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“…The overall processing task even collapses if any process fails [1]. If each linear machine can form as an individual motion control system and it has the controller, sensor, and drives of its own, then the linear machines can work cooperatively by the communications among the local controllers from each linear machine, then the ultimate global task for the processing job can be accomplished, without requiring any high-level supervisory administration or decision [2].…”

Section: Introductionmentioning

confidence: 99%

“…Current coordination strategies focus on the design and optimization of the lower-level, cooperative tracking control algorithms to improve the relative error behaviors among all working units [2,3]. However, since tracking coordination control cannot affect the external, independent reference signals, the relative error behaviors may deteriorate and the tracking control algorithms even malfunction if all the working units are driven by unrelated, asynchronous reference signals [4].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Distributed Motion Control for Multiple Linear Switched Reluctance Machines

et al. 2017

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This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on the successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

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“…The overall processing task even collapses if any process fails [1]. If each linear machine can form as an individual motion control system and it has the controller, sensor and drives of its own, then the linear machines can work cooperatively, by the communications among the local controllers from each linear machine, then the ultimate global task for the processing job can be accomplished, without requiring any high-level supervisory administration or decision [3]. Since each linear machine belongs to the individual positioning control system locally, the machine accesses its individual reference signal.…”

Section: Introductionmentioning

confidence: 99%

“…Current coordination strategies focus on the design and optimization of the lower-level, cooperative tracking control algorithms to improve the relative error behaviors among all working units [2][3]. However, since the tracking coordination control cannot affect the external, independent reference signals, the relative error behaviors may deteriorate and the tracking control algorithms even malfunction if all the working units are driven by unrelated, asynchronous reference signals [4].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Distributed Motion Control for Multiple Linear Switched Reluctance Machines

Zhang¹,

Yuan²,

Luo³

et al. 2017

Preprint

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This paper investigates a distributed, coordinated motion control network based on multiple direct-drive, linear switched reluctance machines (LSRMs). A hierarchical, two-level synchronization control strategy is proposed for the four LSRMs based motion control network. The high-level, reference signals agreement algorithm is first employed to correct the asynchronous behaviors of the position commands. Then, the low-level tracking synchronization method is applied for the collaborative position control of the four LSRMs. The proposed two-level, fault-tolerant control strategy eliminates the asynchrony of the reference signals and it also guarantees the coordinated tracking control performance of the four LSRMs. Experimental results demonstrate that effective coordinated tracking control can be ensured, based on successful agreement of reference signals and an absolute tracking error falling within 2 mm can be achieved.

show abstract

Lyapunov, Adaptive, and Optimal Design Techniques for Cooperative Systems on Directed Communication Graphs

Cited by 592 publications

References 34 publications

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

Hierarchical Distributed Motion Control for Multiple Linear Switched Reluctance Machines

Hierarchical Distributed Motion Control for Multiple Linear Switched Reluctance Machines

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