Global optimization approach to nonlinear optimal control

To determine the optimum in nonlinear optimal control problems, it is proposed to convert the continuous problems into a form suitable for nonlinear programming (NLP). Since the resulting finite-dimensional NLP problems can present multiple local optima, a global optimization approach is developed where random starting conditions are improved by using special line searches. The efficiency, speed, and reliability of the proposed approach is examined by using two examples.Financial support from the Natural Science and Engineering Research Council under Grant A-3515 as well as an Ontario Graduate Scholarship are gratefully acknowledged. All the computations were done with the facilities of the University of Toronto Computer Centre and the Ontario Centre for Large Scale Computations.