Adaptive trajectory generation based on real-time estimated parameters for impaired aircraft landing. Issue 15 (18th November 2019)

• Record Type: Journal Article
• Authors: Hong, Haichao; Maity, Arnab; Holzapfel, Florian; Tang, Shengjing
• Is Part Of: International journal of systems science. Volume 50:Issue 15(2019)
• Page Start: 2733
• Page End: 2751
• Publication Date: 2019-11-18
• Subjects: Generalized model predictive static programming -- adaptive trajectory generation -- damaged aircraft guidance -- parameter estimation -- aircraft emergency landing -- flight safety; System analysis -- Periodicals; 003.3
• DOI: 10.1080/00207721.2019.1675099
• Languages: English
• ISSNs: 0020-7721

Abstract

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.