Abstract
Results are presented which permit a more efficient solution of optimal parameter selection problems by constrained mathematical programming algorithms of the gradient type. The central result is a relationship which is established between the first variation (directional derivative) of the cost functional with respect to the parameter vector and an integral over the planning period of the gradient of a hamiltonian with respect to the parameter vector. The evaluation of the cost functional and the first variation requires the solution of a system of only 2n+l differential equations, where n is the number of state equations.
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