Research On Intelligent Trajectory Optimization And Guidance Method Of Reentry Vehicle

Gliding reentry vehicle(GRV)is a type of aircraft,which is launched from the ground,enters the atmosphere through the ascending section,and return to a predetermined target eventually.The GRV has the characteristics of high lift-to-drag ratio,rapid maneuverability,and accurate reach in a wide range.As a result,it has broad application prospects in both military and civilian fields,which also makes it a hot focus and inevitable trend in the future development of spacecraft.During the entire flight process,many factors have introduced a lot of interference for the trajectory optimization and guidance system.These factors include the complexity of the aerodynamic environment,the uncertainty of the initial state,and the influence of errors caused by its own observations.Based on the dynamic model and software simulation platform,this paper focuses on the reentry vehicle,and takes the optimizing and tracking the trajectory as the research purpose.The following research work has been carried out and completed:Firstly,this paper studies and analyzes the force and motion law of the reentry aircraft in the glide phase,introduces the three-degree-of-freedom dynamics equation on the basis of reasonable assumptions,and conducts dimensionless processing of its state variables.Due to the uncertainty of the time interval in the flight process,a dynamic equation with inverse energy as the independent variable is established,which lays the foundation for the subsequent work.Then,the constraints that need to be met during the flight process are clarified,and the re-entry corridor formed by the process constraints can be obtained.Finally,a scientific and effective standard atmospheric environment model is introduced.Next,research and introduce an intelligent trajectory optimization method based on improved differential evolution.The multiple shooting method is used to discretize the control and state variables of the trajectory optimization problem.Then,based on the triangle mutation rule,an improved differential evolution algorithm that can improve the diversity and convergence speed of the population is obtained.In order to balance the global search ability and the local search ability,the improved differential evolution algorithm is combined with the standard differential evolution algorithm,and which algorithm to choose is determined based on the principle of non-linear decreasing probability.Finally,multiple sets of comparative simulations are performed to verify the effectiveness and robustness of the algorithm.Research and introduce a linear quadratic regulator(LQR)guidance method based on analytic hierarchy process(AHP)to select weight matrix.Aiming at the non-linear and fast time-varying characteristics of the reentry aircraft model,a small deviation linearization process is performed at each moment balance point of the nominal trajectory.Secondly,the basic principles of AHP and LQR are introduced.AHP is used to select the weight matrix of LQR.Finally,the effectiveness and robustness of the method are verified through comparative simulations under different pull deviations and Monte Carlo shooting simulation.At last,research and introduce a numerical prediction correction guidance method based on altitude compensation.The basic ideas and principles of the predictive correction guidance method are explained firstly.Then,due to the uncertainty of flight time,the inverse energy is introduced as the new independent variable of the dynamic equation.The penalty function is used to process the constraints and transform the original problem.For longitudinal guidance,the functional relationship between the control quantity and energy is represented by the segmented pitch profile,and the absolute value of the pitch angle is obtained by Gauss-Newton search iteration.For lateral guidance,the course angle deviation corridor is used to determine the sign of the control quantity.The control value is compensated according to the quasi-balanced gliding conditions,and the purpose is to offset the large-scale oscillation of the altitude during the flight.Finally,the comparison and Monte Carlo simulation results under different deviations are verified and analyzed.