Constrained trajectory optimization using migrant particle swarm optimization algorithm

A novel PSO algorithm, the Migrant Particle Swarm Optimization (Migrant PSO), is presented to solve the trajectory optimization problem in the presence of constraints such as dynamic pressure and overload. Imitating the behaviour of a flock of migrant birds, the Migrant PSO algorithm employs stochastic search method and adaptive linear search method respectively for PSO search spaces including both continuous space and discrete space. In the example of the minimum peak heat rate reentry trajectory optimization for X-33 vehicle model with free terminal time, some key problems such as parameterized method are argued in detail. The simulation results indicate that the Migrant PSO algorithm proves to be able to generate a complete and optimal 3DOF reentry trajectory rapidly.