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An On-Line LearningAlgorithm of Parallel Mode for MLPN Models

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Book cover Advances in Neural Networks – ISNN 2007 (ISNN 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4492))

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Abstract

An on-line learning algorithm in parallel mode for multi-layer perceptron network (MLPN) model is proposed. The MLPN is on-line trained directly in a parallel mode. The on-line learning algorithm is based on the Extended Kalman Filter (EKF) algorithm. This network is able to learn the non-linear dynamic behaviour of unknown time-varying systems and perform multi-step-ahead prediction for control purpose. The performance of this model is evaluated in modelling a multi-variable non-linear continuous stirred tank reactor (CSTR).

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References

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Author information

Authors and Affiliations

  1. Control Systems Research Group, Liverpool John Moores University, UK

    D. L. Yu & T. K. Chang

  2. Department of Automation, Northeast University at Qinhuangdao, China

    D. W. Yu

Authors
  1. D. L. Yu
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  2. T. K. Chang
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  3. D. W. Yu
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Editor information

Derong Liu Shumin Fei Zengguang Hou Huaguang Zhang Changyin Sun

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© 2007 Springer Berlin Heidelberg

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Yu, D.L., Chang, T.K., Yu, D.W. (2007). An On-Line LearningAlgorithm of Parallel Mode for MLPN Models. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_52

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  • DOI: https://doi.org/10.1007/978-3-540-72393-6_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72392-9

  • Online ISBN: 978-3-540-72393-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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