Deterministic Global Optimization in Nonlinear Optimal Control Problems
 William R. Esposito,
 Christodoulos A. Floudas
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The accurate solution of optimal control problems is crucial in many areas of engineering and applied science. For systems which are described by a nonlinear set of differentialalgebraic equations, these problems have been shown to often contain multiple local minima. Methods exist which attempt to determine the global solution of these formulations. These algorithms are stochastic in nature and can still get trapped in local minima. There is currently no deterministic method which can solve, to global optimality, the nonlinear optimal control problem. In this paper a deterministic global optimization approach based on a branch and bound framework is introduced to address the nonlinear optimal control problem to global optimality. Only mild conditions on the differentiability of the dynamic system are required. The implementation of the approach is discussed and computational studies are presented for four control problems which exhibit multiple local minima.
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 Title
 Deterministic Global Optimization in Nonlinear Optimal Control Problems
 Journal

Journal of Global Optimization
Volume 17, Issue 14 , pp 97126
 Cover Date
 20000901
 DOI
 10.1023/A:1026578104213
 Print ISSN
 09255001
 Online ISSN
 15732916
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 Differentialalgebraic equations
 Global optimization
 Optimal control
 Industry Sectors
 Authors

 William R. Esposito ^{(1)}
 Christodoulos A. Floudas ^{(1)}
 Author Affiliations

 1. Department of Chemical Engineering, Princeton University, Princeton, USA