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Adaptive Data Based Modelling and Estimation with Application to Real Time Vehicular Collision Avoidance

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2773))

Abstract

The majority of control and estimation algorithms are based upon linear time invariant models of the process, yet many dynamic processes are nonlinear, stochastic and non-stationary. In this presentation an online data based modelling and estimation approach is described which produces parsimonious dynamic models, which are transparent and appropriate for control and estimation applications. These models are linear in the adjustable parameters – hence are provable, real time and transparent but exponential in the input space dimension. Several approaches are introduced – including automatic structure algorithms to reduce the inherent curse of dimensionality of the approach. The resultant algorithms can be interpreted in rule based form and therefore offer considerable transparency to the user as to the underlying dynamics, equally the user can control the resultant rule base during learning. These algorithms will be applied to (a) helicopter flight control (b) auto-car driving and (c) multiple ship guidance and control.

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References

  1. Harris, C.J., Hong, X., Gan, Q.: Adaptive Modelling Estimation and Fusion from Data. Springer, Berlin (2002)

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  2. Chen, S., Hong, D., Harris, C.J.: Sparse multioutput rbf network construction using combined locally regularised OLS & D Optimality. In: IEE Proc. CTA, vol. 150(2), pp. 139–146 (March 2002)

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  3. Hong, X., Harris, C.J., Chen, S.: Robust neurofuzzy model knowledge extraction. To appear Trans. IEEE SMC (2003)

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Author information

Authors and Affiliations

  1. Department of Electronics and Computer Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK

    Chris J. Harris

Authors
  1. Chris J. Harris
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Editor information

Editors and Affiliations

  1. Computing Laboratory, Oxford University, Parks Road, OXI 3QD, United Kingdom

    Vasile Palade

  2. Intelligent Systems and Signal Processing Labs, Moulsecoomb, University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, Mawson Lakes, University of South Australia, 5095, Adelaide, SA, Australia

    Lakhmi Jain

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© 2003 Springer-Verlag Berlin Heidelberg

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Harris, C.J. (2003). Adaptive Data Based Modelling and Estimation with Application to Real Time Vehicular Collision Avoidance. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_3

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  • DOI: https://doi.org/10.1007/978-3-540-45224-9_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40803-1

  • Online ISBN: 978-3-540-45224-9

  • eBook Packages: Springer Book Archive

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