Trajectory optimization of hypersonic vehicles based on adaptive receding horizon optimization and alternating direction multiplier method with time coordination

A fusion method based on adaptive rolling horizon optimization (ARHO) and alternating direction multiplier method (ADMM) is proposed for the trajectory optimization of hypersonic vehicles (HVs) cooperative arrive mission with time coordination. Firstly, a hypersonic vehicle (HV) dynamic model is constructed and constraints such as heat flow, dynamic pressure, overload, no-fly zone avoidance and collision avoidance are defined. Secondly, the weighted objective function is designed to form the optimal control problem. Then, the ARHO method transforms the global optimization problem into local optimization within an overlapping sliding window, dramatically reduces the computational complexity and realizes the time domain decomposition. Collaborative variables and dual variables are introduced by ADMM, which transforms HVs coupling constraints into single HV problem constraints, achieving distributed parallel solution and spatial domain decouple. The convergence of the method is proved. The results of a single simulation show that three HVs can reach the target point simultaneously while satisfying all constraints. Monte Carlo simulations show that the mission success rate is 97.3% in random cases, demonstrating good stochastic environment adaptability.