An event-triggered moving horizon estimation strategy is proposed for spacecraft pose estimation.The error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled model...An event-triggered moving horizon estimation strategy is proposed for spacecraft pose estimation.The error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled model.In order to reduce the energy consumption on spacecraft,an event-triggered moving horizon estimator(MHE)is designed for real-time pose estimation with limited communication resources.The model mismatch caused by event-triggered is finally solved by solving the cost function of the min-max optimization problem.The system simulation model is built in Matlab/Simulink,and the spacecraft pose estimation simulation is carried out.The numerical results demonstrate that the designed estimator could ensure the estimation effect and save spacecraft communication and computing resources effectively.展开更多
Accurate state estimations are perquisites of autonomous navigation and orbit maintenance missions.The extended Kalman lter(EKF)and the unscented Kalman lter(UKF),are the most commonly used method.However,the EKF resu...Accurate state estimations are perquisites of autonomous navigation and orbit maintenance missions.The extended Kalman lter(EKF)and the unscented Kalman lter(UKF),are the most commonly used method.However,the EKF results in poor estimation performance for systems are with high nonlinearity.As for the UKF,irregular sampling instants are required.In addition,both the EKF and the UKF cannot treat constraints.In this paper,a symplectic moving horizon estimation algorithm,where constraints can be considered,for nonlinear systems are developed.The estimation problem to be solved at each sampling instant is seen as a nonlinear constrained optimal control problem.The original nonlinear problem is transferred into a series of linear-quadratic problems and solved iteratively.A symplectic method based on the variational principle is proposed to solve such linear-quadratic problems,where the solution domain is divided into sub-intervals,and state,costate,and parametric variables are locally interpolated with linear approximation.The optimality conditions result in a linear complementarity problem which can be solved by the Lemke's method easily.The developed symplectic moving horizon estimation method is applied to the Earth-Moon L2 libration point navigation.And numerical simulations demonstrate that though more time-consuming,the proposed method results in better estimation performance than the EKF and the UKF.展开更多
文摘An event-triggered moving horizon estimation strategy is proposed for spacecraft pose estimation.The error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled model.In order to reduce the energy consumption on spacecraft,an event-triggered moving horizon estimator(MHE)is designed for real-time pose estimation with limited communication resources.The model mismatch caused by event-triggered is finally solved by solving the cost function of the min-max optimization problem.The system simulation model is built in Matlab/Simulink,and the spacecraft pose estimation simulation is carried out.The numerical results demonstrate that the designed estimator could ensure the estimation effect and save spacecraft communication and computing resources effectively.
基金The authors are grateful for the nancial support of the National Natural Science Foundation of China(Grant No.11772074).
文摘Accurate state estimations are perquisites of autonomous navigation and orbit maintenance missions.The extended Kalman lter(EKF)and the unscented Kalman lter(UKF),are the most commonly used method.However,the EKF results in poor estimation performance for systems are with high nonlinearity.As for the UKF,irregular sampling instants are required.In addition,both the EKF and the UKF cannot treat constraints.In this paper,a symplectic moving horizon estimation algorithm,where constraints can be considered,for nonlinear systems are developed.The estimation problem to be solved at each sampling instant is seen as a nonlinear constrained optimal control problem.The original nonlinear problem is transferred into a series of linear-quadratic problems and solved iteratively.A symplectic method based on the variational principle is proposed to solve such linear-quadratic problems,where the solution domain is divided into sub-intervals,and state,costate,and parametric variables are locally interpolated with linear approximation.The optimality conditions result in a linear complementarity problem which can be solved by the Lemke's method easily.The developed symplectic moving horizon estimation method is applied to the Earth-Moon L2 libration point navigation.And numerical simulations demonstrate that though more time-consuming,the proposed method results in better estimation performance than the EKF and the UKF.
