Authors: Takeshi Tsuchiya
Publish Date: 2011/10/21
Volume: 54, Issue: 4, Pages: 831-854
Abstract
In this paper we propose a new deterministic global optimization method for solving nonlinear optimal control problems in which the constraint conditions of differential equations and the performance index are expressed as polynomials of the state and control functions The nonlinear optimal control problem is transformed into a relaxed optimal control problem with linear constraint conditions of differential equations a linear performance index and a matrix inequality condition with semidefinite programming relaxation In the process of introducing the relaxed optimal control problem we discuss the duality theory of optimal control problems polynomial expression of the approximated value function and sumofsquares representation of a nonnegative polynomial By solving the relaxed optimal control problem we can obtain the approximated global optimal solutions of the control and state functions based on the degree of relaxation Finally the proposed global optimization method is explained and its efficacy is proved using an example of its application
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