Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72464
Title: Adaptive neural network control of flexible link robots based on singular perturbation
Authors: Ge, S.S. 
Lee, T.H. 
Tan, E.G.
Issue Date: 1997
Source: Ge, S.S.,Lee, T.H.,Tan, E.G. (1997). Adaptive neural network control of flexible link robots based on singular perturbation. IEEE Conference on Control Applications - Proceedings : 365-370. ScholarBank@NUS Repository.
Abstract: In this paper, an adaptive neural network controller is presented for flexible link robots (FLR) using the singular perturbation technique. The complex full model of FLR can be decomposed into two separate time scale subsystems by modelling the elastic forces as the fast variables and the joint variables as the slow variables. A composite control strategy is adopted to control the two-time scale model with the slow subsystem being controlled by a neural network controller. The weights of the NNs are updated on-line based on direct adaptive techniques. A robust control term is also added for closed-loop stability. The fast subsystem is stabilized by a simple LQR control around the equilibrium trajectory defined by the slow subsystem.
Source Title: IEEE Conference on Control Applications - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/72464
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