This paper proposes a hybrid sequential second-order cone programming(HSSOCP)method with a three-layer scheme for the entry trajectory optimization of the cross-domain morphing vehicles(CDMVs).By defining the new morp...This paper proposes a hybrid sequential second-order cone programming(HSSOCP)method with a three-layer scheme for the entry trajectory optimization of the cross-domain morphing vehicles(CDMVs).By defining the new morphing rate control variable and using relaxation techniques to relax the bank angle constraint,the SOCP-based entry problem is constructed.A dynamic relaxation penal-ization technique is developed in the first layer to overcome artificial infeasibility and significantly enhance initialization robustness.A novel standard oscillation identification(SOI)method is proposed to precisely identify the iteration oscillations of basic SSOCP in the second layer,which can significantly improve the solution accuracy.A soft-trust-region strategy is applied in the third layer to eliminate oscillations and accelerate convergence.Simulation results of two scenarios demonstrate that the proposed SOI method effectively avoids non-standard oscillation interference versus traditional methods.The morphing aircraft can complete tasks better with a 7.01%and 10.43%reduction in heat load respectively compared to fixed-wing aircraft.The HSSOCP method can maintain accuracy while reducing computation time by 63.47%and 73.86%versus VATSSOCP.Monte Carlo simulations further validate the robustness.展开更多
This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(C...This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(CDMVs).The decoupling of states and controls for complex nonlinear dynamics is achieved by defining new control and state variables.A series of sub convex problems is formulated by successive linearization and discretization of the constraints.The proposed Trust-region Sequential Convex Programming(TSCP)scheme consists of three stages:an initial guess generation stage,a basic solution stage,and an optimal solution stage.An approach to penalize the dynamic relaxation is firstly developed to obtain an initial guess with considerable accuracy and significantly improve the robustness of the algorithm by overcoming the drawbacks of potential artificial infeasibility.The oscillation phenomenon of the TSCP method under rectangular trust region is then investigated,and a novel N-shape-based oscillation identification method is proposed to identify the oscillation accurately.Finally,an oscillation-avoidance method based on the sort trust-region is proposed to improve the convergence of the TSCP algorithm.Numerical comparisons of the proposed method and a typical TSCP method,as well as the morphing and fixed-morphing vehicles are provided to demonstrate the effectiveness and efficiency of the proposed method and the performance advantages of the morphing vehicle.The robustness of the method is further verified by Monte Carlo simulation.展开更多
To evaluate the heat performance of the lifting-body entry vehicle during the hypersonic gliding phase,entry flight heat tests involving the determination of the maximum peak-heat-flux entry trajectory with complex co...To evaluate the heat performance of the lifting-body entry vehicle during the hypersonic gliding phase,entry flight heat tests involving the determination of the maximum peak-heat-flux entry trajectory with complex constraints are essential.A significant obstacle is the uncertainty of passage time or energy states of the maximum peak entry heat flux point and waypoints.This paper showcases an endeavour to leverage disjunctive programming and combinatorial theory for the max-max type(maximum peak-heat-flux)Entry Trajectory Optimization(ETO)problems with complex constraints such as dynamic pressure,normal load,waypoints,and no-fly zones.The concept of a"generalized waypoint"is introduced,and the maximum peak-heat-flux point is regarded as a"generalized waypoint".Through the application of propositional calculus rules,the derivation of generalized waypoints incorporating various physical quantities and magnitudes such as heat flux density,longitude,and latitude is actualized in one disjunctive normal form,enabling resolution via a unified method.Consequently,a novel method based on combinatorial prior rules is proposed,utilizing Successive Mixed-Integer Nonlinear Programming(SMINLP)to optimize various heat entry test flight trajectories.Numerical experiments are provided to show the computational accuracy,stability,and adaptability of the proposed method in solving maxmax type entry optimal control problems.展开更多
基金supported by the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission(No.LASAT-2022-A03).
摘要This paper proposes a hybrid sequential second-order cone programming(HSSOCP)method with a three-layer scheme for the entry trajectory optimization of the cross-domain morphing vehicles(CDMVs).By defining the new morphing rate control variable and using relaxation techniques to relax the bank angle constraint,the SOCP-based entry problem is constructed.A dynamic relaxation penal-ization technique is developed in the first layer to overcome artificial infeasibility and significantly enhance initialization robustness.A novel standard oscillation identification(SOI)method is proposed to precisely identify the iteration oscillations of basic SSOCP in the second layer,which can significantly improve the solution accuracy.A soft-trust-region strategy is applied in the third layer to eliminate oscillations and accelerate convergence.Simulation results of two scenarios demonstrate that the proposed SOI method effectively avoids non-standard oscillation interference versus traditional methods.The morphing aircraft can complete tasks better with a 7.01%and 10.43%reduction in heat load respectively compared to fixed-wing aircraft.The HSSOCP method can maintain accuracy while reducing computation time by 63.47%and 73.86%versus VATSSOCP.Monte Carlo simulations further validate the robustness.
基金supported by the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission,China(No.LASAT-2022-A03)。
摘要This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(CDMVs).The decoupling of states and controls for complex nonlinear dynamics is achieved by defining new control and state variables.A series of sub convex problems is formulated by successive linearization and discretization of the constraints.The proposed Trust-region Sequential Convex Programming(TSCP)scheme consists of three stages:an initial guess generation stage,a basic solution stage,and an optimal solution stage.An approach to penalize the dynamic relaxation is firstly developed to obtain an initial guess with considerable accuracy and significantly improve the robustness of the algorithm by overcoming the drawbacks of potential artificial infeasibility.The oscillation phenomenon of the TSCP method under rectangular trust region is then investigated,and a novel N-shape-based oscillation identification method is proposed to identify the oscillation accurately.Finally,an oscillation-avoidance method based on the sort trust-region is proposed to improve the convergence of the TSCP algorithm.Numerical comparisons of the proposed method and a typical TSCP method,as well as the morphing and fixed-morphing vehicles are provided to demonstrate the effectiveness and efficiency of the proposed method and the performance advantages of the morphing vehicle.The robustness of the method is further verified by Monte Carlo simulation.
基金funded by the Key Laboratory of Cross-Domain Flight Interdisciplinary Technology,China(No.2024-KF02201)the National Natural Science Foundation of China(No.61973326)。
摘要To evaluate the heat performance of the lifting-body entry vehicle during the hypersonic gliding phase,entry flight heat tests involving the determination of the maximum peak-heat-flux entry trajectory with complex constraints are essential.A significant obstacle is the uncertainty of passage time or energy states of the maximum peak entry heat flux point and waypoints.This paper showcases an endeavour to leverage disjunctive programming and combinatorial theory for the max-max type(maximum peak-heat-flux)Entry Trajectory Optimization(ETO)problems with complex constraints such as dynamic pressure,normal load,waypoints,and no-fly zones.The concept of a"generalized waypoint"is introduced,and the maximum peak-heat-flux point is regarded as a"generalized waypoint".Through the application of propositional calculus rules,the derivation of generalized waypoints incorporating various physical quantities and magnitudes such as heat flux density,longitude,and latitude is actualized in one disjunctive normal form,enabling resolution via a unified method.Consequently,a novel method based on combinatorial prior rules is proposed,utilizing Successive Mixed-Integer Nonlinear Programming(SMINLP)to optimize various heat entry test flight trajectories.Numerical experiments are provided to show the computational accuracy,stability,and adaptability of the proposed method in solving maxmax type entry optimal control problems.