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Command Filtering-Based Adaptive Fuzzy Control of Flexible-Joint Robots With Time-Varying Full-State Constraints

Yu Zhu, Jiapeng Liu, Jinpeng Yu, Qing‐Guo Wang

2023IEEE Transactions on Circuits & Systems II Express Briefs18 citationsDOI

Abstract

This brief is concerned with trajectory tracking control for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> -link flexible-joint robots (FJR) with time-varying full-state constraints and uncertain dynamics. The barrier Lyapunov functions are constructed to avoid the violation of time-varying constraints. The fuzzy logic systems are used to deal with unknown nonlinearities in FJR systems. The “explosion of complexity” problem in the traditional backstepping method is overcomed by introducing command filtered control with error compensation, and an adaptive fuzzy command filtered control scheme based on time-varying barrier Lyapunov function is designed. The stability of the closed-loop system is analyzed using Lyapunov theory. Simulation results show that the proposed method can guarantee the full-state constraints and position tracking accuracy of the system.

Topics & Concepts

Joint (building)Control theory (sociology)State (computer science)Computer scienceFuzzy logicFuzzy control systemControl (management)RobotAdaptive controlControl engineeringArtificial intelligenceEngineeringAlgorithmStructural engineeringAdaptive Control of Nonlinear SystemsIterative Learning Control SystemsControl and Dynamics of Mobile Robots
Command Filtering-Based Adaptive Fuzzy Control of Flexible-Joint Robots With Time-Varying Full-State Constraints | Litcius