Hybrid neural fuzzy sliding mode control of flexible-joint manipulators with unknown dynamics
In this paper, a hybrid neural fuzzy control scheme is proposed for the control of flexible-joint robot manipulators with unknown dynamics. The control strategy is based on a feed-forward artificial neural network to partially approximate the manipulator's inverse dynamics. A fuzzy sliding mode feedback controller is also used for the online adaptation of the neural network-based controller. Simulation results of various scenarios highlight the performance and stability of the proposed controller in compensating for the highly nonlinear unknown dynamics of the manipulator under different dynamical conditions and external disturbances.
|Conference||IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics|
Chaoui, H, Gueaieb, W. (Wail), Yagoub, M.C.E. (Mustapha C. E.), & Sicard, P. (Pierre). (2006). Hybrid neural fuzzy sliding mode control of flexible-joint manipulators with unknown dynamics. In IECON Proceedings (Industrial Electronics Conference) (pp. 4082–4087). doi:10.1109/IECON.2006.348032