Please use this identifier to cite or link to this item:
|Title:||Constructive learning control based on function approximation and wavelet|
|Authors:||Xu, J.-X. |
|Citation:||Xu, J.-X., Yan, R. (2004). Constructive learning control based on function approximation and wavelet. Proceedings of the IEEE Conference on Decision and Control 5 : 4952-4957. ScholarBank@NUS Repository. https://doi.org/10.1109/CDC.2004.1429591|
|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 ad hoc processes in pre-setting the network size.|
|Source Title:||Proceedings of the IEEE Conference on Decision and Control|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 11, 2018
checked on Feb 25, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.