Existence conditions and applications of shifting sliding mode control

Zhou, Jun; Hagiwara, Toru

doi:10.1109/cdc.2001.981090

Cited by 5 publications

(1 citation statement)

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“…To address the trajectory-tracking aspect, the navigation features of the leader-average dynamics are exploited. More specifically, based on the sliding mode control techniques [6], [12], [36], [37], [44], [56], [61], the transient/steady-state average dynamics are manipulated for the leader-average state to slide on the sliding surface specified along the tracked trajectory, while the flexible formation is retained simultaneously. Advantages of the approach include: (a) the control algorithms for flexible formation and sliding mode can be designed separately; (b) the sliding mode control for navigation keeps the trajectory tracking from matched noise, while the average trajectory-tracking is attainable in finite time; (c) the sliding mode is virtual, and no chattering control actions are practically involved.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Trajectory-Tracking Flexible Formation via Generalized Flocking and Leader-Average Sliding Mode Control

Zhou

Zeng

2020

IEEE Access

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This paper reports a flexible (or time-varying) multi-agent formation approach with average trajectory tracking for second-order integral multi-agent networks with single virtual leaders. The approach is developed by means of time-varying Olfati-Saber flocking algorithms, and sliding mode control (SMC) in terms of the leader-average dynamics. More precisely, SMC-specifying average trajectory tracking is combined with flexible multi-agent flocking driven by the Olfati-Saber flocking algorithms with timevarying weighting norm. Existence conditions and properties of the suggested multi-agent formation are examined rigorously, together with implementation formulas. It is shown that by designing the sliding surface and the time-varying weighting matrix appropriately, flexible formation with finite-time trajectory tracking can be achieved, free of control action chattering; moreover, the sliding mode control and formation control can be designed separately. Numerical examples are given to illustrate the main results. INDEX TERMS Multi-agent, flexible flocking formation, leader-average model, sliding mode control, trajectory tracking.

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Section: Introductionmentioning

confidence: 99%

Multi-Agent Trajectory-Tracking Flexible Formation via Generalized Flocking and Leader-Average Sliding Mode Control

Zhou

Zeng

2020

IEEE Access

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Sliding mode tracking for pneumatic muscle actuators in bicep/tricep pair configuration

Liang

Lilly

Proceedings of the 2003 American Control Conference, 2003.

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This paper presents robust motion control of pneumatic muscle actuators arranged in bicepltricep pair configuration ,to deal with system and environmental uncertainties using the sliding mode approach.A mathematical model is.derived 3or an arm.with PMs in bicepltricep pair configuration. A sliding mode controller is designed to yield asymptotic tracking of elbow angle. The results of simulations are presented to demonstrate the success of the proposed controller. : . ' . , .

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Computational analysis for the synchronizing time of the microcar transmission

Tian

Tang

et al. 2011

2011 International Conference on Electric Information and Control Engineering

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Existence conditions and applications of shifting sliding mode control

Cited by 5 publications

References 7 publications

Multi-Agent Trajectory-Tracking Flexible Formation via Generalized Flocking and Leader-Average Sliding Mode Control

Multi-Agent Trajectory-Tracking Flexible Formation via Generalized Flocking and Leader-Average Sliding Mode Control

Sliding mode tracking for pneumatic muscle actuators in bicep/tricep pair configuration

Computational analysis for the synchronizing time of the microcar transmission

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