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A new information-weighted recursive algorithm for time-varying systems: application to UAV system identification

Author

Listed:
  • Zun Liu
  • Honghai Ji
  • Hailong Pei
  • Frank L. Lewis

Abstract

This paper presents a new recursive identification method which can efficiently estimate time-varying parameters in discrete time systems and has significant advantages over standard recursive least-squares (RLS) method. This new information-weighted recursive algorithm for time-varying systems has three novel features, discounting of inaccurate estimates through weighting by the Information matrix, using the reuse of past data in computing current parameter estimates, a new tuneable damping factor parameter and a precisely designed compensation term to neutralise the estimation error caused by time-varying coefficients. A rigorous proof of convergence is also provided. Simulations show that the new algorithm significantly outperforms standard RLS, exhibiting better tracking performance and faster convergence. Flight tests on a T-REX 800 helicopter Unmanned Aerial Vehicle platform show that it gives system parameter estimates that are accurate enough and converge quickly enough that flight controllers can be designed in real-time based on the online identified model.

Suggested Citation

  • Zun Liu & Honghai Ji & Hailong Pei & Frank L. Lewis, 2018. "A new information-weighted recursive algorithm for time-varying systems: application to UAV system identification," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(11), pages 2477-2489, August.
  • Handle: RePEc:taf:tsysxx:v:49:y:2018:i:11:p:2477-2489
    DOI: 10.1080/00207721.2018.1505004
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