Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20383
Title: Fuzzy neural control of systems with unknown dynamic using Q-learning strategies
Authors: Kwok, DP
Deng, ZD
Li, CK
Leung, TP
Sun, ZQ
Wong, JCK
Keywords: Adaptive control
Cerebellar model arithmetic computers
Fuzzy control
Fuzzy neural nets
Learning (artificial intelligence)
Neurocontrollers
PH control
Step response
Issue Date: 2003
Publisher: IEEE
Source: The 12th IEEE International Conference on Fuzzy Systems, 2003 : FUZZ '03, 25-28 May 2003, v. 1, p. 482-487 How to cite?
Abstract: In this paper an efficient Q-learning paradigm implemented on a fuzzy CMAC network is proposed. The fuzzy CMAC network topological architecture is described. The continuous states of the system are partitioned into a number of fuzzy boxes. With the proposed fuzzy CMAC the Q-values of agents in the fired fuzzy boxes are evaluated and the control actions with maximum Q-values can be derived. The proposed hybrid adaptive and learning type of Fuzzy Neural control system based on the Q-learning is applied to the control of a pH-neutralization process.
URI: http://hdl.handle.net/10397/20383
ISBN: 0-7803-7810-5
DOI: 10.1109/FUZZ.2003.1209411
Appears in Collections:Conference Paper

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