Open AccessAscent Guidance Based on Onboard Trajectory Regeneration for Vehicles With a Combined Cycle Engine
Author(s) -
Xiangji Tang,
Zhaoting Li,
Hongbo Zhang
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3124972
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
For a vehicle with a combined cycle engine, an ascent guidance method based on onboard trajectory regeneration is proposed to meet the requirements of adaptability and robustness. This method combines onboard trajectory planning with reference trajectory tracking and modifies the computational model. In the onboard trajectory planning, a hierarchical receding horizon optimization is developed to update the reference trajectory depending on the current state. Further, the optimization problem subject to multiple constraints is solved by an improved segmented pseudospectral method, in which a recursive initialization strategy is introduced to improve the computational efficiency for onboard application. In reference trajectory tracking, the active disturbance rejection control theory is used to improve the robustness of the tracking process. Based on the theory, an extended state observer for the multi-input and multi-output system is designed to estimate the state and the disturbance. Then, the trajectory tracking law is derived by linearizing the model with dynamic compensation. Besides, the scale factors of the dynamic system are defined to compensate for the uncertainty of the model, and an online estimation method is used to identify the parameters. Numerical simulation validates the efficiency of the proposed method.