Trajectory Optimization Using Collocation And Evolutionary Programming For Constrained Nonlinear Dynamical Systems

TRAJECTORY OPTIMIZATION USING COLLOCATION AND EVOLUTIONARY PROGRAMMING FOR CONSTRAINED NONLINEAR DYNAMICAL SYSTEMS Brandon Merle Shippey, MS The University of Texas at Arlington, 2008 Supervising Professor: Kamesh Subbarao Trajectory design and optimization has a broad variety of applications in fields such as aerospace and electrical engineering. The solution of a trajectory that minimizes a cost function subject to nonlinear differential equations of motion and various types of constraints may be obtained by the methods of optimal control theory. A framework is presented for numerical solution of the optimal control problem. The solution is converted to that of a constrained discrete parameter optimization problem. Direct collocation and nonlinear programming are used to perform a local gradientbased search for the optimal solution. A genetic algorithm combined with a shooting method conducts a global search of the solution space to provide a near-optimal, nearfeasible initialization for the nonlinear program. The framework is applied to three minimum-time case studies: i) a path planning problem for two mobile robots with obstacle avoidance; ii) an aircraft turning maneuver; iii) a low-thrust interplanetary transfer.

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