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Fully Distributed Scaled Consensus Tracking of High-Order Multiagent Systems With Time Delays and Disturbances

Zheng Zhang, Shiming Chen, Yuanshi Zheng

2021IEEE Transactions on Industrial Informatics152 citationsDOI

Abstract

This article focuses on scaled consensus tracking for a class of high-order nonlinear multiagent systems. Different from the existing results, for high-order nonlinear multiagent systems with time delays and external disturbances, a fully distributed consensus protocol is designed to drive all agents to achieve scaled consensus with preassigned ratios. The control gains are varying and updated by distributed adaptive laws. As a result, the presented protocol is independent of any global information, and thus, could be implemented in a fully distributed manner. Simultaneously, the fully distributed control protocol using an adaptive <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sigma$</tex-math></inline-formula> -modification technique is presented to deal with external disturbances, which can guarantee the tracking errors and coupling weights of all following agents are uniformly ultimately bounded. To tackle with the derivatives of the functionals with time delays, the Lyapunov–Krasovskii functional is employed to analyze and compensate them by introducing multiintegral terms. Finally, simulation examples are included to verify the effectiveness of the theoretical results.

Topics & Concepts

Multi-agent systemNonlinear systemProtocol (science)Bounded functionConsensusControl theory (sociology)Tracking (education)Computer scienceController (irrigation)Adaptive controlClass (philosophy)NotationDistributed computingTracking errorOrder (exchange)Control (management)Mathematical optimizationMathematicsArtificial intelligencePsychologyMedicineFinancePathologyAgronomyArithmeticQuantum mechanicsPhysicsMathematical analysisAlternative medicineBiologyEconomicsPedagogyDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationAdaptive Control of Nonlinear Systems