Optimal control of nonlinear systems with model-reality differences

Dynamic integrated system optimization and parameter estimation (DISOPE) is used to develop a method for solving nonlinear optimal control problems where the model employed to compute the optimal solution is different from reality. An iterative procedure is described which achieves the correct real solution despite model-reality differences. Results which extend earlier work on steady-state optimal control under model-reality differences to dynamic optimal control are presented.<
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