Adaptive neural control for an uncertain robotic manipulator with joint space constraints

DOI10.1080/00207179.2015.1135351zbMath1353.93080OpenAlexW2275947424MaRDI QIDQ2954027

Keng Peng Tee, Unnamed Author, Wei He, Shuzhi Sam Ge

Publication date: 11 January 2017

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

Full work available at URL: https://doi.org/10.1080/00207179.2015.1135351

zbMATH Keywords

neural networksbackstepping designintegral barrier Lyapunov functionalsjoint space constraintsunknown robot dynamics

Mathematics Subject Classification ID

Queues and service in operations research (90B22) Nonlinear systems in control theory (93C10) Lyapunov and storage functions (93D30) Adaptive control/observation systems (93C40) Automated systems (robots, etc.) in control theory (93C85) Control/observation systems governed by ordinary differential equations (93C15)

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Cites Work

• Barrier Lyapunov functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints
• Barrier Lyapunov functions for the control of output-constrained nonlinear systems
• A robust adaptive nonlinear control design
• An adaptive neural network switching control approach of robotic manipulators for trajectory tracking
• Control of nonlinear systems with partial state constraints using a barrier Lyapunov function
• Persistency of Excitation in Identification Using Radial Basis Function Approximants
• Adaptive output feedback control for a class of nonlinear systems with full-state constraints
• Adaptive Jacobian Tracking Control of Robots With Uncertainties in Kinematic, Dynamic and Actuator Models

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