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2008

Hierarchical Fuzzy CMAC for Nonlinear Systems Modeling

9 years 21 days ago
Hierarchical Fuzzy CMAC for Nonlinear Systems Modeling
Abstract--Since the fuzzy cerebellar model articulation controller (FCMAC) uses linguistic variables, it is highly intuitive and easily comprehended. Despite the FCMAC's good local generalization capability for approximating nonlinear functions and fast learning, a normal FCMAC requires huge memory, and its dimension increases exponentially with the number of inputs. In order to overcome the memory explosion problem, this paper proposes two types of hierarchical FCMAC (HFCMAC). Another contribution of the paper is that we give stable learning algorithms for these two HFCMACs. Backpropagation-like approach is applied to train each block with a time-varying learning rate, which is obtained by the input-to-state stability technique.
Wen Yu, Floriberto Ortiz Rodriguez, Marco A. Moren
Added 29 Dec 2010
Updated 29 Dec 2010
Type Journal
Year 2008
Where TFS
Authors Wen Yu, Floriberto Ortiz Rodriguez, Marco A. Moreno-Armendariz
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