Abstract
A novel iterative procedure is described for solving optimal control problems subject to nonlinear differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original nonlinear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations. A hierarchical structure of the algorithm is described where parallel subsystem optimal control problems are solved. Optimality and convergence aspects are discussed and a simulation example is provided to illustrate the performance of the technique.
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