TY - JOUR
T1 - Finite-Horizon Optimal Tracking Guidance for Aircraft Based on Approximate Dynamic Programming
AU - Wan, Shizheng
AU - Chang, Xiaofei
AU - Li, Quancheng
AU - Yan, Jie
N1 - Publisher Copyright:
© 2019 Shizheng Wan et al.
PY - 2019
Y1 - 2019
N2 - Referring to the optimal tracking guidance of aircraft, the conventional time based kinematics model is transformed into a downrange based model by independent variable replacement. The deviations of in-flight altitude and flight path angle are penalized and corrected to achieve high precision tracking of reference trajectory. The tracking problem is solved as a linear quadratic regulator applying small perturbation theory, and the approximate dynamic programming method is used to cope with the solving of finite-horizon optimization. An actor-critic structure is established to approximate the optimal tracking controller and minimum cost function. The least squares method and Adam optimization algorithm are adopted to learn the parameters of critic network and actor network, respectively. A boosting trajectory with maximum final velocity is generated by Gauss pseudospectral method for the validation of guidance strategy. The results show that the trained feedback control parameters can effectively resist random wind disturbance, correct the initial altitude and flight path angle deviations, and achieve the goal of following a given trajectory.
AB - Referring to the optimal tracking guidance of aircraft, the conventional time based kinematics model is transformed into a downrange based model by independent variable replacement. The deviations of in-flight altitude and flight path angle are penalized and corrected to achieve high precision tracking of reference trajectory. The tracking problem is solved as a linear quadratic regulator applying small perturbation theory, and the approximate dynamic programming method is used to cope with the solving of finite-horizon optimization. An actor-critic structure is established to approximate the optimal tracking controller and minimum cost function. The least squares method and Adam optimization algorithm are adopted to learn the parameters of critic network and actor network, respectively. A boosting trajectory with maximum final velocity is generated by Gauss pseudospectral method for the validation of guidance strategy. The results show that the trained feedback control parameters can effectively resist random wind disturbance, correct the initial altitude and flight path angle deviations, and achieve the goal of following a given trajectory.
UR - http://www.scopus.com/inward/record.url?scp=85064089838&partnerID=8YFLogxK
U2 - 10.1155/2019/8649781
DO - 10.1155/2019/8649781
M3 - 文章
AN - SCOPUS:85064089838
SN - 1024-123X
VL - 2019
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
M1 - 8649781
ER -