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EnglishIn this paper we present a robust adaptive controller based on a neural network (NN) for a variable stiffness actuator (VSA). The controller is able to independently set the mechanical stiffness and position at the joint shaft to guarantee robustness with respect to slowly time-varying and unmodeled friction coefficients affecting the dynamics of the actuator. The lumped uncertainties of the VSA including unmodeled dynamics are considered and approximated by a simple NN so that the controlled system is asymptotically stable, and remains effective while process conditions vary. To cope with the reconstruction error of the NN, a sliding mode like additional robust control term is introduced. The proofs for the uniformly ultimately bounded (UUB) and uniform asymptotic (UAS) stabilities for the closed-loop system are provided in detail via Lyapunov theory. Simulation and experimental results are reported in support of both validity and performance of the proposed approach.
| Titolo: | Neural network based robust adaptive control for a variable stiffness actuator |
| Autori interni: | |
| Anno del prodotto: | 2008 |
| Abstract: | In this paper we present a robust adaptive controller based on a neural network (NN) for a variable stiffness actuator (VSA). The controller is able to independently set the mechanical stiffness and position at the joint shaft to guarantee robustness with respect to slowly time-varying and unmodeled friction coefficients affecting the dynamics of the actuator. The lumped uncertainties of the VSA including unmodeled dynamics are considered and approximated by a simple NN so that the controlled system is asymptotically stable, and remains effective while process conditions vary. To cope with the reconstruction error of the NN, a sliding mode like additional robust control term is introduced. The proofs for the uniformly ultimately bounded (UUB) and uniform asymptotic (UAS) stabilities for the closed-loop system are provided in detail via Lyapunov theory. Simulation and experimental results are reported in support of both validity and performance of the proposed approach. |
| Handle: | http://hdl.handle.net/11568/120855 |
| ISBN: | 9781424425044 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11568/120855
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