Parallel processing of optimal-control problems by dynamic programming

Abstract A method is presented for the parallel evaluation of optimal-control problems using an iterative method of dynamic programming. The procedure is based on the application of the interaction prediction principle by which the global optimal-control problem is reduced to the optimization of subproblems. Each of these problems is locally optimized using successive approximations of single-variable state-increment dynamic-programming problems. Examples of the parallel solution of multivariable, constrained, nonlinear problems for which the computation is carried out on a microcomputer are given.

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