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Adaptive Finite-Time Containment Control of Uncertain Multiple Manipulator Systems

Lin Zhao, Jinpeng Yu, Qing‐Guo Wang

2020IEEE Transactions on Cybernetics66 citationsDOI

Abstract

This article is concerned with the containment control of multiple manipulators with uncertain parameters. A novel distributed adaptive backstepping strategy is given in the finite-time control framework. The finite-time command filters (FTCFs) used in the strategy can avoid the explosion of complexity problem for conventional backstepping. To further improve the control performance, the filtering errors caused by the used FTCFs are removed by using the error compensation mechanism (ECM). The proposed virtual control signal, the control torque, and the adaptive updating law can guarantee the set tracking errors converge to an adjustable neighborhood of the origin in finite time in the presence of uncertain parameters. Because the virtual control signal and ECM only use the local information, the established method is completely distributed. Two simulation examples are given to show the effectiveness of the proposed scheme.

Topics & Concepts

BacksteppingControl theory (sociology)Compensation (psychology)Computer scienceContainment (computer programming)Adaptive controlSIGNAL (programming language)Control (management)Set (abstract data type)Scheme (mathematics)Tracking errorControl engineeringEngineeringMathematicsArtificial intelligencePsychologyPsychoanalysisProgramming languageMathematical analysisAdaptive Control of Nonlinear SystemsDistributed Control Multi-Agent SystemsControl and Dynamics of Mobile Robots
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