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Adaptive trajectory generation based on real-time estimated parameters for impaired aircraft landing

Author

Listed:
  • Haichao Hong
  • Arnab Maity
  • Florian Holzapfel
  • Shengjing Tang

Abstract

This paper is motivated by a need to address the challenge of securing a safe landing after suffering from inflight impairment. In this paper, a new adaptive generalised model predictive static programming (G-MPSP) is developed to generate a safe emergency landing trajectory for impaired aircraft. Utilising the computationally efficient G-MPSP framework, the proposed algorithm enables adaptation of model parameters based on the prediction errors to ensure reasonable guidance performance. Based on the estimated parameters, a feasible landing trajectory is then generated by the flexible finite-horizon G-MPSP with input constraints. The integrated approach features explicit closed-form solutions for both parameter estimation and trajectory generation. Its effectiveness is demonstrated by simulations in the presence of parameter uncertainties and noises and by comparison studies with the non-adaptive G-MPSP.

Suggested Citation

  • Haichao Hong & Arnab Maity & Florian Holzapfel & Shengjing Tang, 2019. "Adaptive trajectory generation based on real-time estimated parameters for impaired aircraft landing," International Journal of Systems Science, Taylor & Francis Journals, vol. 50(15), pages 2733-2751, November.
    • Handle: RePEc:taf:tsysxx:v:50:y:2019:i:15:p:2733-2751
    DOI: 10.1080/00207721.2019.1675099
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