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Adaptive Finite-Time Command Filtered Controller Design for Nonlinear Systems With Output Constraints and Input Nonlinearities

Kun Wang, Xiaoping Liu, Yuanwei Jing

2021IEEE Transactions on Neural Networks and Learning Systems33 citationsDOI

Abstract

This work addresses a finite-time tracking control issue for a class of nonlinear systems with asymmetric time-varying output constraints and input nonlinearities. To guarantee the finite-time convergence of tracking errors, a novel finite-time command filtered backstepping approach is presented by using the command filtered backstepping technique, finite-time theory, and barrier Lyapunov functions. The newly proposed method can not only reduce the complexity of computation of the conventional backstepping control and compensate filtered errors caused by dynamic surface control but also can ensure that the output variables are restricted in compact bounding sets. Moreover, the proposed controller is applied to robot manipulator systems, which guarantees the practical boundedness of all the signals in the closed-loop system. Finally, the effectiveness and practicability of the developed control strategy are validated by a simulation example.

Topics & Concepts

BacksteppingControl theory (sociology)Controller (irrigation)Nonlinear systemConvergence (economics)Computer scienceBounding overwatchLyapunov functionComputationNonlinear controlAdaptive controlMathematicsControl engineeringControl (management)EngineeringAlgorithmArtificial intelligenceAgronomyEconomic growthBiologyEconomicsQuantum mechanicsPhysicsAdaptive Control of Nonlinear SystemsIterative Learning Control SystemsControl and Dynamics of Mobile Robots
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