Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00521-003-0380-1
Title: Adaptive robust control for servo manipulators
Authors: Khoh, C.J.
Tan, K.K. 
Keywords: Adaptive control
Manipulators
Neural network
Robust control
Stability
Issue Date: Dec-2003
Source: Khoh, C.J., Tan, K.K. (2003-12). Adaptive robust control for servo manipulators. Neural Computing and Applications 12 (3-4) : 178-184. ScholarBank@NUS Repository. https://doi.org/10.1007/s00521-003-0380-1
Abstract: In this paper, an adaptive robust control scheme is developed which is suitable for the control of a class of uncertain nonlinear systems, typical of many servo manipulators. The control scheme is comprised of a model reference adaptive controller (MRAC) augmented with a nonlinear compensator based on an adaptive radial basis function (RBF). The RBF compensator is used to neutralise the effects of uncertain and possibly nonlinear dynamics, so that the equivalent system as seen by the MRAC is reduced to one without significant unstructured modelling errors. A stability analysis is provided to show the uniform stability and the asymptotic tracking capabilities of the proposed control system. Real-time experiment results verify the effectiveness of the control scheme.
Source Title: Neural Computing and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/54935
ISSN: 09410643
DOI: 10.1007/s00521-003-0380-1
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