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Active Disturbance Rejection Control for Networked Switched Nonlinear Systems With Decentralized Event-Triggered Communication

Yiwen Qi, Simeng Zhang, Choon Ki Ahn

2022IEEE Transactions on Systems Man and Cybernetics Systems17 citationsDOI

Abstract

Uncertainty and disturbance are always the first issues to deal with in any networked system. Considering these factors, the active disturbance rejection control (ADRC) for networked switched systems (NSSs) with decentralized event-triggered communication was investigated in this study. This is the first time a comprehensive analysis and synthesis method for the ADRC of NSSs has been proposed. The technical contribution is mainly divided into two categories. On the one hand, a novel parameter-dependent switching constraint is proposed, which solves the problem of ADRC-based switching law construction and settles the complex coupling between switching, event-triggering, and ADRC components. On the other hand, triggering the output of linear extended state observer (LESO) rather than its input can result in a more accurate estimation, while reasonably configuring network resources. Accordingly, a new tight bound of the high gain adjustment parameter of the observer was obtained. In addition, the stability analysis and state convergence region calculations for switched ADRC systems are given. Finally, the effectiveness of the proposal is demonstrated by simulation.

Topics & Concepts

Control theory (sociology)Active disturbance rejection controlState observerConstraint (computer-aided design)Convergence (economics)Computer scienceObserver (physics)Nonlinear systemStability (learning theory)State (computer science)Telecommunications networkDecentralised systemEvent (particle physics)Control (management)Control engineeringEngineeringArtificial intelligenceTelecommunicationsAlgorithmMachine learningQuantum mechanicsEconomic growthMechanical engineeringEconomicsPhysicsStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationDistributed Control Multi-Agent Systems
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