Adaptive Trajectory Tracking Algorithm for the Aerospace Vehicle Based on Improved T-MPSP

Chao Ou, Chengjun Shan, Zhongtao Cheng and Yaosong Long ()
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Chao Ou: School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Chengjun Shan: School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Zhongtao Cheng: School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Yaosong Long: School of Aerospace Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Mathematics, 2023, vol. 11, issue 9, 1-16

Abstract: To deal with the uncertainty and disturbance that exist in the tracking system of an aerospace vehicle, an adaptive trajectory-tracking method based on a novel tracking model predictive static programming (T-MPSP) is proposed. Firstly, to make the proposed method more adaptive to uncertain parameter deviations, an extended Kalman filter (EKF) parameter correction strategy is designed. Then, the control constraints are considered to form a novel T-MPSP algorithm. By combining the parameter correction strategy with the improved T-MPSP algorithm, a novel adaptive tracking guidance scheme is presented. Finally, simulations are carried out to demonstrate the effectiveness of the proposed method.

Keywords: trajectory tracking; uncertainty; extended kalman filter; adaptive; control constraints; T-MPSP (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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