A design of CMAC-based fuzzy logic controller with fast learning and accurate approximation
SCIE
SCOPUS
- Title
- A design of CMAC-based fuzzy logic controller with fast learning and accurate approximation
- Authors
- Kim, D
- Date Issued
- 2002-01-01
- Publisher
- ELSEVIER SCIENCE BV
- Abstract
- This paper proposes a CMAC-based fuzzy logic controller (FLC) with a fast learning capability and an accurate approximation ability. The proposed CMAC-based FLC has the fast learning capability because it pursuits the local generalization and only a small number of activated units in the network are participated in the forward and backward computation. It also produces an accurate input-output approximation ability, because it adjusts the MFs model parameters of the input and output variables simultaneously and it considers both centers and widths of output membership functions to compute a crisp defuzzified value. Application to the truck backer-upper control problem of the proposed CMAC-based FLC is presented. Simulation results validate the fast learning and the accurate approximation of the proposed CMAC-based FLC. (C) 2002 Elsevier Science B.V. All rights reserved.
- Keywords
- fuzzy logic controller; cerebellar model articulation controller; backpropagation learning; truck backer-upper control; SYSTEM
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/19244
- DOI
- 10.1016/S0165-0114(00)00102-0
- ISSN
- 0165-0114
- Article Type
- Article
- Citation
- FUZZY SETS AND SYSTEMS, vol. 125, no. 1, page. 93 - 104, 2002-01-01
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.