Neural adaptive global stability control for robot manipulators with time‐varying output constraints

DOI10.1002/rnc.4690zbMath1430.93114OpenAlexW2965728600WikidataQ127393727 ScholiaQ127393727MaRDI QIDQ5208277

Tongtong Kang, Chenguang Yang, Yongqing Fan, Wen-Qing Wang

Publication date: 15 January 2020

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rnc.4690

zbMATH Keywords

adaptive controlrobot manipulatorradial basis function neural network (RBFNN)time-varying constraintsglobal uniformly ultimately bounded (GUUB)

Mathematics Subject Classification ID

Adaptive control/observation systems (93C40) Automated systems (robots, etc.) in control theory (93C85) Adaptive or robust stabilization (93D21)

Related Items (7)

Distributed fixed‐time optimization for multi‐agent systems with time‐varying objective function ⋮ Model‐based event‐triggered neural learning control for discrete‐time strict‐feedback systems ⋮ Observer‐based event and self‐triggered adaptive output feedback control of robotic manipulators ⋮ Observer‐based adaptive neural output‐feedback event‐triggered control for discrete‐time nonlinear systems using variable substitution ⋮ Dynamic learning‐based event‐triggered control of strict‐feedback systems with finite‐time prescribed performance ⋮ Learning‐based robust neuro‐control: A method to compute control Lyapunov functions ⋮ Cooperative learning event‐triggered control for discrete‐time nonlinear multi‐agent systems by internal and external interaction topology

This page was built for publication: Neural adaptive global stability control for robot manipulators with time‐varying output constraints