Please use this identifier to cite or link to this item: https://doi.org/10.1109/IJCNN.2004.1380891
Title: An adaptive learning control approach based on constructive function approximation
Authors: Xu, J.-X. 
Yan, R.
Issue Date: 2004
Citation: Xu, J.-X.,Yan, R. (2004). An adaptive learning control approach based on constructive function approximation. IEEE International Conference on Neural Networks - Conference Proceedings 3 : 1853-1858. ScholarBank@NUS Repository. https://doi.org/10.1109/IJCNN.2004.1380891
Abstract: A constructive function approximation approach is proposed for adaptive learning control which handles finite interval tracking problems. Unlike the well established adaptive neural control which uses a fixed neural network structure as a complete system, in our method the function approximation network consists of a set of bases and the number of bases can be increased when learning repeats. The nature of basis allows the continuously adaptive tuning or learning of parameters when the network undergoes a structure change, consequently offers the flexibility in tuning the network structure. The expansibility of the basis ensures the function approximation accuracy, and removes the processes in p re-setting the network size. Two classes of system unknown nonlinear functions, either in ℒ 2(R) or a known upperbound, are taken into consideration. With the help of Lyapunov method, the existence of solution and the convergence property of the proposed adaptive learning control system, are analyzed rigorously.
Source Title: IEEE International Conference on Neural Networks - Conference Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/83459
ISBN: 0780383591
ISSN: 10987576
DOI: 10.1109/IJCNN.2004.1380891
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