Particle swarm with domain partition and control assignment for time-optimal maneuvers

A novel approach has been proposed for planning time-optimal maneuvers imposing a bang–bang external control. The optimizer was based on the particle swarm optimization and only required setting the maximum number of switches allowed for each axis. Two different test cases were analyzed and solved to validate the optimizer. In the first example, characterized by four state-space variables and no path constraints, the convergence toward the optimal solution has been demonstrated with different values of the maximum number of switches. For the second example, described by six state-space variables and nonlinear path constraints, the optimal solution was reached in more than 70% of the cases over 100 simulations, path constraints were completely satisfied, and errors on the final conditions were lower than 10-8 in normalized units. The computational effort was rather small because about 2000 iterations were required to reach convergence. Moreover, the second example has shown that the solution obtained with the described method could be better than the solutions obtained with pseudospectral optimization algorithms.