Abstract
An efficient numerical procedure for solving mixed-integer optimal control (MIOPCON) problems is developed in this paper, which involves a decomposition strategy through a series of optimal control and mixed-integer linear programming (MILP) subproblems. The optimal control problem is defined by fully implicit differential-algebraic equations, which are substituted by discrete time implicit equations resulting from the integration of the system equations by an implicit Runge-Kutta method. The advantage of this approach is that the dual information necessary for the MILP master problem can be obtained directly from the adjoint variables of the optimal control primal problem. As a result the MIOPCON problem is solved only in the reduced space, enabling efficient application of the algorithm to problems described by large-scale differential algebraic equations.
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