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Re-entry trajectory optimization using a multiple- interval Radau pseudospectral method 被引量:5

Re-entry trajectory optimization using a multiple- interval Radau pseudospectral method
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摘要 Aiming at increasing the calculation efficiency of the pseudospectral methods, a multiple- interval Radau pseudospectral method (RPM) is presented to generate a reusable launch vehicle (RLV) 's optimal re-entry trajectory. After dividing the optimal control problem into many intervals, the state and control variables are approximated using many fixed- and low-degree Lagrange polyno- mials in each interval. Convergence of the numerical discretization is then achieved by increasing the number of intervals. With the application of the proposed method, the normal nonlinear program- ming (NLP) problem transcribed from the optimal control problem can avoid being dense because of the low-degree approximation polynomials in each interval. Thus, the NLP solver can easily compute a solution. Finally, simulation results show that the optimized re-entry trajectories satisfy the path constraints and the boundary constraints successfully. Compared with the single interval RPM, the multiple-interval RPM is significantly faster and has higher calculation efficiency. The results indicate that the multiple-interval RPM can be applied for real-time trajectory generation due to its high effi- ciency and high precision. Aiming at increasing the calculation efficiency of the pseudospectral methods, a multiple- interval Radau pseudospectral method (RPM) is presented to generate a reusable launch vehicle (RLV) 's optimal re-entry trajectory. After dividing the optimal control problem into many intervals, the state and control variables are approximated using many fixed- and low-degree Lagrange polyno- mials in each interval. Convergence of the numerical discretization is then achieved by increasing the number of intervals. With the application of the proposed method, the normal nonlinear program- ming (NLP) problem transcribed from the optimal control problem can avoid being dense because of the low-degree approximation polynomials in each interval. Thus, the NLP solver can easily compute a solution. Finally, simulation results show that the optimized re-entry trajectories satisfy the path constraints and the boundary constraints successfully. Compared with the single interval RPM, the multiple-interval RPM is significantly faster and has higher calculation efficiency. The results indicate that the multiple-interval RPM can be applied for real-time trajectory generation due to its high effi- ciency and high precision.
出处 《Journal of Beijing Institute of Technology》 EI CAS 2013年第1期20-27,共8页 北京理工大学学报(英文版)
关键词 reusable launch vehicle (RLV) trajectory optimization calculation efficiency multi-pie-interval Radau pseudospectral method (RPM) reusable launch vehicle (RLV) trajectory optimization calculation efficiency multi-pie-interval Radau pseudospectral method (RPM)
作者简介 Author for correspondence E-mail: hanpeng@ bit. edu. cn
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