Neural network adaptive control design for robot manipulators under velocity constraints

DOI10.1016/j.jfranklin.2017.11.036zbMath1384.93069OpenAlexW2771171862WikidataQ106760971 ScholiaQ106760971MaRDI QIDQ1707839

Hamed Rahimi Nohooji, Lei Cui, I. C. Howard

Publication date: 4 April 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/20.500.11937/59850

zbMATH Keywords

adaptive controlneural networkLyapunov functionsrobot manipulatorsinput saturationuncertain dynamicsvelocity constraints

Mathematics Subject Classification ID

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) Artificial intelligence for robotics (68T40)

Related Items (9)

Constrained neural adaptive PID control for robot manipulators ⋮ Event-triggered zeroing dynamics for motion control of Stewart platform ⋮ Continuous PID-SMC based on improved EHGO for robot manipulators with limited state measurements ⋮ Backstepping Nussbaum gain dynamic surface control for a class of input and state constrained systems with actuator faults ⋮ Adaptive tracking control for a class of manipulator systems with state constraints and stochastic disturbances ⋮ Predefined-time robust contour tracking of robotic manipulators ⋮ Impulse-dependent settling-time for finite time stabilization of uncertain impulsive static neural networks with leakage delay and distributed delays ⋮ Robust adaptive control for prescribed performance tracking of constrained uncertain nonlinear systems ⋮ A novel controller for nonlinear uncertain systems using a combination of SDRE and function approximation technique: regulation and tracking of flexible-joint manipulators

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