Analytical reentry guidance framework based on swarm intelligence optimization and altitude-energy profile
Hui Ling Xu, Guangbin Cai, Chaoxu Mu, Xin Li
Abstract
Aimed at improving the real-time performance of guidance instruction generation, an analytical hypersonic reentry guidance framework is presented. The key steps of the novel guidance framework are the parameterization of reentry guidance problems and the optimization of parameters. First, a quintic polynomial function of energy was designed to describe the altitude profile. Then, according to the altitude-energy profile, the altitude, velocity, flight path angle, and bank angle were obtained analytically, which naturally met the terminal constraints. In addition, the angle of the attack profile was determined using the velocity parameter. The swarm intelligent optimization algorithms were used to optimize the parameters. The path constraints were enforced by the penalty function method. Finally, extensive simulations were carried out in both nominal and dispersed cases, and the simulation results showed that the proposed guidance framework was effective, high-precision, and robust in different scenarios.