Neural adaptive tracking control for an uncertain robot manipulator with time-varying joint space constraints

[Display omitted] •Constrained adaptive neural control is developed for uncertain robot manipulators.•Tangent-type asymmetric and time-varying barrier Lyapunov functions are utilized.•Uncertainties in both manipulator dynamics and actuator dynamics are handled.•The semi-globally uniformly ultimately...

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Bibliographic Details
Published in:Mechanical systems and signal processing 2018-11, Vol.112, p.44-60
Main Authors: N. Rahimi, Hamed, Howard, Ian, Cui, Lei
Format: Article
Language:English
Subjects:
Actuators
Adaptive control
Constraints
Feedback control
Input saturation
Manipulators
Neural networks
Radial basis function neural networks
Robot arms
Robot control
Tangent barrier Lyapunov function
Time-varying asymmetric constraints
Tracking control
Uncertain actuator
Uncertain manipulator
Uncertainty
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Summary:[Display omitted] •Constrained adaptive neural control is developed for uncertain robot manipulators.•Tangent-type asymmetric and time-varying barrier Lyapunov functions are utilized.•Uncertainties in both manipulator dynamics and actuator dynamics are handled.•The semi-globally uniformly ultimately boundedness of all signals is achieved.•The effectiveness of the theoretical developments is verified through simulations. This paper presents a control design for a robotic manipulator with uncertainties in both actuator dynamics and manipulator dynamics subject to asymmetric time-varying joint space constraints. Tangent-type time-varying barrier Lyapunov functionals (tvBLFs) are constructed to ensure no constraint violation and to remove the need for transforming the original constrained system into an equivalent unconstrained one. Adaptive Neural Networks (NNs) are proposed to handle uncertainties in manipulator dynamics and actuator dynamics in addition to the unknown disturbances. Proper input saturation is employed, and it is proved that under the proposed method the stability and semi-global uniform ultimate boundedness of the closed-loop system can be achieved without violation of constraints. The effectiveness of the theoretical developments is verified through numerical simulations.
ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2018.03.042