Dynamic optimization using adaptive control vector parameterization

In this paper we present a method for the optimization of dynamic systems using problem-adapted discretizations. The method is based on the direct sequential or single-shooting approach, where the optimization problem is converted into a nonlinear programming problem by parameterization of the control profiles. A fully adaptive, problem-dependent parameterization is generated by repetitive solution of increasingly refined finite dimensional optimization problems. In each step of the proposed algorithm, the adaptation is based on a wavelet analysis of the solution profiles obtained in the previous step. The method is applied to several case study problems to demonstrate that the adaptive parameterization is more efficient and robust compared to a uniform parameterization of comparable accuracy.