Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/69918
Title: Development of feedback error learning strategies for training neurofuzzy controllers on-line
Authors: Tan, W.W. 
Lo, C.H.
Issue Date: 2001
Source: Tan, W.W.,Lo, C.H. (2001). Development of feedback error learning strategies for training neurofuzzy controllers on-line. IEEE International Conference on Fuzzy Systems 2 : 1016-1021. ScholarBank@NUS Repository.
Abstract: Neurofuzzy model-based controllers have been successfully applied in practice. This paper reviews the feedback error learning strategies used for training neurofuzzy controllers on-line. The objective is to identify the weaknesses of existing algorithms. A variation of the feedback error learning strategy, capable of overcoming these limitations, is then proposed. Simulation results are presented to show that the proposed feedback error learning equation is able to quickly train the neurofuzzy controller to provide tight setpoint tracking. Another advantage is that the neurofuzzy controller that employs the proposed on-line learning mechanism can be commissioned easily.
Source Title: IEEE International Conference on Fuzzy Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/69918
Appears in Collections:Staff Publications

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