Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/61759
Title: Adaptive neural network control of flexible joint manipulators in constrained motion
Authors: Ge, S.S. 
Woon, L.C.
Keywords: Adaptive
Constrained motion
Flexible joint manipulators
Neural network
Issue Date: 1998
Source: Ge, S.S.,Woon, L.C. (1998). Adaptive neural network control of flexible joint manipulators in constrained motion. Transactions of the Institute of Measurement and Control 20 (1) : 37-45. ScholarBank@NUS Repository.
Abstract: This paper addresses the control problem of flexible joint manipulators in constrained motion. The singular perturbation method is applied to reduce the original system into slow and fast subsystems. By adopting the composite control strategy, an adaptive neural network controller is first developed to control the slow subsystem. Then a fast feedback control is designed to stabilise the fast subsystem along its equilibrium trajectory. The system stability is proven using Lyapunov theory. It is shown that the motion tracking error converges to zero asymptotically, whereas the force tracking error remains bounded and can be made arbitrarily small. Numerical simulations are provided to show the effectiveness of the approach.
Source Title: Transactions of the Institute of Measurement and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/61759
ISSN: 01423312
Appears in Collections:Staff Publications

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