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Event-Triggered Fully Distributed H<sub>∞</sub> Containment Control for MASs

Yang Xiao, Wei‐Wei Che

2024IEEE Transactions on Systems Man and Cybernetics Systems27 citationsDOI

Abstract

This article investigates the fully distributed observer-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty}$</tex-math> </inline-formula> containment control problem for multiagent systems (MASs) under the event-triggered strategy. Under this control framework, all followers will eventually converge to the convex hull formed by leaders with prescribed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty}$</tex-math> </inline-formula> performance. First, to reduce the unnecessary network resources consumption, an adaptive dynamic event trigger (DET) strategy is introduced and is rigorously proven to be free of the Zeno behavior. Besides, an output-based state observer is designed to obtain the unmeasured system states. Furthermore, the fully distributed control scheme is developed, namely, only the neighboring information of agents is used to design the controller, the observer, and the event-triggered mechanism. By constructing a new Lyapunov function, the sufficient conditions are derived to guarantee the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty}$</tex-math> </inline-formula> containment control performance of MASs. Finally, a practical physical example is used to demonstrate that the designed control strategy can accomplish the containment control task and ensure the desired <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_{\infty}$</tex-math> </inline-formula> containment control performance simultaneously.

Topics & Concepts

NotationContainment (computer programming)Observer (physics)Event (particle physics)Lyapunov functionController (irrigation)Computer scienceMathematicsAlgorithmDiscrete mathematicsProgramming languageArithmeticPhysicsQuantum mechanicsNonlinear systemBiologyAgronomyDistributed Control Multi-Agent SystemsAdaptive Dynamic Programming ControlReinforcement Learning in Robotics
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