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Fuzzy CMAC with Online Learning Ability and Its Application

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Book cover Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4221))

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Abstract

The binary behavior of activation function in receptive field of conventional cerebellar model articulation controller (CMAC) affects the continuity of the network output. In addition, the original learning scheme of CMAC may corrupt the previous learning data. A control scheme, which parallely combines the fuzzy CMAC (FCMAC) and PID, is proposed in the paper. The weights are updated according to the credits which are assigned to the hypercubers according to their learning histories and fuzzy membership degrees. The FCMAC is powerful in control time-varying processes due to the online learning ability of the FCMAC. Experimental results of temperature control have shown that the FCMAC with online learning ability can accurately follow the control trajectory and reduce the tracking errors.

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Author information

Authors and Affiliations

  1. Mechanical Engineering School, Tianjin University, 92 weijin Road, Nankai Division, Tianjin City, China

    Shixia Lv, Gang Wang, Zhanhui Yuan & Jihua Yang

Authors
  1. Shixia Lv
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  2. Gang Wang
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  3. Zhanhui Yuan
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  4. Jihua Yang
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., 710071, Xi’an, P.R. China

    Xin-bo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Lv, S., Wang, G., Yuan, Z., Yang, J. (2006). Fuzzy CMAC with Online Learning Ability and Its Application. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_15

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  • DOI: https://doi.org/10.1007/11881070_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45901-9

  • Online ISBN: 978-3-540-45902-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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