A GLOBALLY CONVERGENT, LOCALLY OPTIMAL MIN-H ALGORITHM FOR HYBRID OPTIMAL CONTROL

摘要

Existing algorithms for the indirect solution of hybrid optimal control problems suffer from several deficiencies: Min-H algorithms are not applicable to hybrid systems and are not globally convergent. Indirect multiple shooting and indirect collocation are difficult to initialize and have a small domain of convergence. Contrary to these existing algorithms, a novel min-H algorithm is introduced here, which is initialized intuitively and converges globally to a locally optimal solution. The algorithm solves hybrid optimal control problems with autonomous switching, a fixed sequence of discrete states, and unspecified switching times. Furthermore, the convergence of the proposed algorithm is at least quadratic near the optimum, and solutions are found with high accuracy. A numerical example shows the efficiency of the novel min-H algorithm.