Neural network adaptive control design for robot manipulators under velocity constraints
This paper studies the neural adaptive control design for robotic systems with uncertain dynamics under the existence of velocity constraints and input saturation. The control objective is achieved by choosing a control Lyapunov function using joint error variables that are restricted to linear grow...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/59850 |
| _version_ | 1848760557281214464 |
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| author | Rahimi Nohooji, Hamed Howard, Ian Cui, Lei |
| author_facet | Rahimi Nohooji, Hamed Howard, Ian Cui, Lei |
| author_sort | Rahimi Nohooji, Hamed |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper studies the neural adaptive control design for robotic systems with uncertain dynamics under the existence of velocity constraints and input saturation. The control objective is achieved by choosing a control Lyapunov function using joint error variables that are restricted to linear growth and furthermore by introducing a secant type barrier Lyapunov function for constraining the joint rate variables. The former is exploited to bind the forward propagation of the position errors, and the latter is utilized to impose hard bounds on the velocity. Effective input saturation is expressed, and neural networks are employed to tackle the uncertainty problem in the system dynamics. Feasibility conditions are formulated, and the optimal design parameters are obtained by solving the constrained optimization problem. We prove that under the proposed method, semi-global uniform ultimate boundedness of the closed-loop system can be guaranteed. Tracking errors meanwhile converge to small neighborhoods of the origin, and violations of predefined velocity constraints are avoided. Finally, numerical simulations are performed to verify the effectiveness of the theoretical developments. |
| first_indexed | 2025-11-14T10:17:40Z |
| format | Journal Article |
| id | curtin-20.500.11937-59850 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:17:40Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-598502020-09-07T05:32:46Z Neural network adaptive control design for robot manipulators under velocity constraints Rahimi Nohooji, Hamed Howard, Ian Cui, Lei This paper studies the neural adaptive control design for robotic systems with uncertain dynamics under the existence of velocity constraints and input saturation. The control objective is achieved by choosing a control Lyapunov function using joint error variables that are restricted to linear growth and furthermore by introducing a secant type barrier Lyapunov function for constraining the joint rate variables. The former is exploited to bind the forward propagation of the position errors, and the latter is utilized to impose hard bounds on the velocity. Effective input saturation is expressed, and neural networks are employed to tackle the uncertainty problem in the system dynamics. Feasibility conditions are formulated, and the optimal design parameters are obtained by solving the constrained optimization problem. We prove that under the proposed method, semi-global uniform ultimate boundedness of the closed-loop system can be guaranteed. Tracking errors meanwhile converge to small neighborhoods of the origin, and violations of predefined velocity constraints are avoided. Finally, numerical simulations are performed to verify the effectiveness of the theoretical developments. 2017 Journal Article http://hdl.handle.net/20.500.11937/59850 10.1016/j.jfranklin.2017.11.036 Elsevier fulltext |
| spellingShingle | Rahimi Nohooji, Hamed Howard, Ian Cui, Lei Neural network adaptive control design for robot manipulators under velocity constraints |
| title | Neural network adaptive control design for robot manipulators under velocity constraints |
| title_full | Neural network adaptive control design for robot manipulators under velocity constraints |
| title_fullStr | Neural network adaptive control design for robot manipulators under velocity constraints |
| title_full_unstemmed | Neural network adaptive control design for robot manipulators under velocity constraints |
| title_short | Neural network adaptive control design for robot manipulators under velocity constraints |
| title_sort | neural network adaptive control design for robot manipulators under velocity constraints |
| url | http://hdl.handle.net/20.500.11937/59850 |