Multi-Process Integrated Planning and Guidance for Return of Reusable Aircraft Under Time Constraint

As the launch frequency of reusable launch vehicle (RLV) increases, the requirement of landing site management is increasing. Especially, the return flight time of RLV should be constrained to improve the utilization of landing site. In this paper, a multi-process integrated (MPI) planning and guida...

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Published in:	IEEE access Vol. 8; pp. 179823 - 179836
Main Authors:	Wei, Chang-Zhu, Zhang, Ze, Li, Yuan, Li, Yongyuan
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Acceleration Aerodynamics Aircraft guidance Algorithms backward calculation Computational geometry Computer simulation Constraints convex optimization Convexity Earth Error correction Flight time improved predictor-corrector guidance Interpolation Landing Mathematical analysis Mission planning Monte Carlo simulation Optimization Particle swarm optimization Planning Prediction algorithms Predictor-corrector methods range estimation Reusable launch vehicles RLV time constraint Time factors Trajectory Trajectory optimization Trigonometric functions
ISSN:	2169-3536, 2169-3536
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Abstract	As the launch frequency of reusable launch vehicle (RLV) increases, the requirement of landing site management is increasing. Especially, the return flight time of RLV should be constrained to improve the utilization of landing site. In this paper, a multi-process integrated (MPI) planning and guidance algorithm for deorbit phase and reentry phase is proposed to meet the mission requirement of RLV. Firstly, the states of RLV at reentry point and deorbit point are given by MPI planning algorithm through inverse calculation. To be specific, by taking the terminal state as the initial value, the reentry point is obtained by the backward calculation based on a cosine-quadratic bank angle profile. According to the relationship among the reentry point, the deorbit time and the deorbit range, the parameters of deorbit phase can be calculated by efficient interpolation based on deorbit ability analysis. The bank angle profile is adjusted to make estimated total flight range approximate the predefined total range by particle swarm optimization algorithm. After that, guidance algorithm considering the terminal position and time constraints of the whole flight phase is given, and the trajectory optimization problem related to brake angle and start-up time is transformed into a series of convex optimization problems in deorbit phase, which can be solved by primal-dual interior-point method with better computational performance and satisfactory accuracy. In the reentry phase, the bank angle profile is designed and updated with improved predictor-corrector algorithm to correct the error during the flight. Finally, the feasibility and robustness of the propose algorithm are verified by multi-mission planning guidance simulation and Monte Carlo simulation.
AbstractList	As the launch frequency of reusable launch vehicle (RLV) increases, the requirement of landing site management is increasing. Especially, the return flight time of RLV should be constrained to improve the utilization of landing site. In this paper, a multi-process integrated (MPI) planning and guidance algorithm for deorbit phase and reentry phase is proposed to meet the mission requirement of RLV. Firstly, the states of RLV at reentry point and deorbit point are given by MPI planning algorithm through inverse calculation. To be specific, by taking the terminal state as the initial value, the reentry point is obtained by the backward calculation based on a cosine-quadratic bank angle profile. According to the relationship among the reentry point, the deorbit time and the deorbit range, the parameters of deorbit phase can be calculated by efficient interpolation based on deorbit ability analysis. The bank angle profile is adjusted to make estimated total flight range approximate the predefined total range by particle swarm optimization algorithm. After that, guidance algorithm considering the terminal position and time constraints of the whole flight phase is given, and the trajectory optimization problem related to brake angle and start-up time is transformed into a series of convex optimization problems in deorbit phase, which can be solved by primal-dual interior-point method with better computational performance and satisfactory accuracy. In the reentry phase, the bank angle profile is designed and updated with improved predictor-corrector algorithm to correct the error during the flight. Finally, the feasibility and robustness of the propose algorithm are verified by multi-mission planning guidance simulation and Monte Carlo simulation.
Author	Wei, Chang-Zhu Li, Yuan Zhang, Ze Li, Yongyuan
Author_xml	– sequence: 1 givenname: Chang-Zhu orcidid: 0000-0001-9279-479X surname: Wei fullname: Wei, Chang-Zhu organization: Harbin Institute of Technology, Harbin, China – sequence: 2 givenname: Ze surname: Zhang fullname: Zhang, Ze organization: Beijing Institute of Control and Electronic Technology, Beijing, China – sequence: 3 givenname: Yuan orcidid: 0000-0003-4421-3000 surname: Li fullname: Li, Yuan email: liyuan@stu.hit.edu.cn organization: Harbin Institute of Technology, Harbin, China – sequence: 4 givenname: Yongyuan surname: Li fullname: Li, Yongyuan organization: Research and Development Center, China Academy of Launch Technology, Beijing, China
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SubjectTerms	Acceleration Aerodynamics Aircraft guidance Algorithms backward calculation Computational geometry Computer simulation Constraints convex optimization Convexity Earth Error correction Flight time improved predictor-corrector guidance Interpolation Landing Mathematical analysis Mission planning Monte Carlo simulation Optimization Particle swarm optimization Planning Prediction algorithms Predictor-corrector methods range estimation Reusable launch vehicles RLV time constraint Time factors Trajectory Trajectory optimization Trigonometric functions
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Title	Multi-Process Integrated Planning and Guidance for Return of Reusable Aircraft Under Time Constraint
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