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Extended Kalman filtering for fuzzy modelling and multi-sensor fusion

Author

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  • G. Rigatos
  • S. Tzafestas

Abstract

Extended Kalman Filtering (EKF) is proposed for: (i) the extraction of a fuzzy model from numerical data; and (ii) the localization of an autonomous vehicle. In the first case, the EKF algorithm is compared to the Gauss--Newton nonlinear least-squares method and is shown to be faster. An analysis of the EKF convergence is given. In the second case, the EKF algorithm estimates the state vector of the autonomous vehicle by fusing data coming from odometric sensors and sonars. Simulation tests show that the accuracy of the EKF-based vehicle localization is satisfactory.

Suggested Citation

  • G. Rigatos & S. Tzafestas, 2007. "Extended Kalman filtering for fuzzy modelling and multi-sensor fusion," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 13(3), pages 251-266, June.
  • Handle: RePEc:taf:nmcmxx:v:13:y:2007:i:3:p:251-266
    DOI: 10.1080/01443610500212468
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    Cited by:

    1. G. Rigatos & N. Zervos, 2017. "Detection of Mispricing in the Black–Scholes PDE Using the Derivative-Free Nonlinear Kalman Filter," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 1-20, June.
    2. Rigatos, Gerasimos G., 2010. "Extended Kalman and Particle Filtering for sensor fusion in motion control of mobile robots," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(3), pages 590-607.
    3. G. Rigatos & P. Siano & T. Ghosh, 2019. "A Nonlinear Optimal Control Approach to Stabilization of Business Cycles of Finance Agents," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1111-1131, March.
    4. G. Rigatos & P. Siano & M. Abbaszadeh & T. Ghosh, 2021. "Nonlinear optimal control of coupled time-delayed models of economic growth," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 375-399, June.
    5. G. Rigatos, 2021. "Statistical Validation of Multi-Agent Financial Models Using the H-Infinity Kalman Filter," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 777-798, October.

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