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 t...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.展开更多
In this study,the problem of time-optimal reconnaissance trajectory design for the aeroassisted vehicle is considered.Different from most works reported previously,we explore the feasibility of applying a high-order a...In this study,the problem of time-optimal reconnaissance trajectory design for the aeroassisted vehicle is considered.Different from most works reported previously,we explore the feasibility of applying a high-order aeroassisted vehicle dynamic model to plan the optimal flight trajectory such that the gap between the simulated model and the real system can be narrowed.A highly-constrained optimal control model containing six-degree-of-freedom vehicle dynamics is established.To solve the formulated high-order trajectory planning model,a pipelined optimization strategy is illustrated.This approach is based on the variable order Radau pseudospectral method,indicating that the mesh grid used for discretizing the continuous system experiences several adaption iterations.Utilization of such a strategy can potentially smooth the flight trajectory and improve the algorithm convergence ability.Numerical simulations are reported to demonstrate some key features of the optimized flight trajectory.A number of comparative studies are also provided to verify the effectiveness of the applied method as well as the high-order trajectory planning model.展开更多
The study of series–parallel plug-in hybrid electric vehicles(PHEVs)has become a research hotspot in new energy vehicles.The global optimal Pareto solutions of energy management strategy(EMS)play a crucial role in th...The study of series–parallel plug-in hybrid electric vehicles(PHEVs)has become a research hotspot in new energy vehicles.The global optimal Pareto solutions of energy management strategy(EMS)play a crucial role in the development of PHEVs.This paper presents a multi-objective global optimization algorithm for the EMS of PHEVs.The algorithm combines the Radau Pseudospectral Knotting Method(RPKM)and the Nondominated Sorting Genetic Algorithm(NSGA)-II to optimize both energy conservation and battery lifespan under the suburban driving conditions of the New European Driving Cycle.The driving conditions are divided into stages at evident mode switching points and the optimal objectives are computed using RPKM.The RPKM results serve as the fitness values in iteration through the NSGA-II method.The results of the algorithm applied to a PHEV simulation show a 26.74%–53.87%improvement in both objectives after 20 iterations compared to the solutions obtained using only RPKM.The proposed algorithm is evaluated against the weighting dynamic programming and is found to be close to the global optimality,with the added benefits of faster and more uniform solutions.展开更多
文摘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.
文摘In this study,the problem of time-optimal reconnaissance trajectory design for the aeroassisted vehicle is considered.Different from most works reported previously,we explore the feasibility of applying a high-order aeroassisted vehicle dynamic model to plan the optimal flight trajectory such that the gap between the simulated model and the real system can be narrowed.A highly-constrained optimal control model containing six-degree-of-freedom vehicle dynamics is established.To solve the formulated high-order trajectory planning model,a pipelined optimization strategy is illustrated.This approach is based on the variable order Radau pseudospectral method,indicating that the mesh grid used for discretizing the continuous system experiences several adaption iterations.Utilization of such a strategy can potentially smooth the flight trajectory and improve the algorithm convergence ability.Numerical simulations are reported to demonstrate some key features of the optimized flight trajectory.A number of comparative studies are also provided to verify the effectiveness of the applied method as well as the high-order trajectory planning model.
基金supported by the Natural Science Foundation of Guangdong Province under Grant 2020A1515010773the Key-Area Research and Development Program of Guangdong Province under Grant 2019B090912001.
文摘The study of series–parallel plug-in hybrid electric vehicles(PHEVs)has become a research hotspot in new energy vehicles.The global optimal Pareto solutions of energy management strategy(EMS)play a crucial role in the development of PHEVs.This paper presents a multi-objective global optimization algorithm for the EMS of PHEVs.The algorithm combines the Radau Pseudospectral Knotting Method(RPKM)and the Nondominated Sorting Genetic Algorithm(NSGA)-II to optimize both energy conservation and battery lifespan under the suburban driving conditions of the New European Driving Cycle.The driving conditions are divided into stages at evident mode switching points and the optimal objectives are computed using RPKM.The RPKM results serve as the fitness values in iteration through the NSGA-II method.The results of the algorithm applied to a PHEV simulation show a 26.74%–53.87%improvement in both objectives after 20 iterations compared to the solutions obtained using only RPKM.The proposed algorithm is evaluated against the weighting dynamic programming and is found to be close to the global optimality,with the added benefits of faster and more uniform solutions.
