Abstract
A state space method of optimal design of dynamic systems subjected to transient loads is developed and applied. In contrast to the conventional nonlinear programming approach of discretizing the time interval and constructing a high dimension nonlinear programming problem, a state space approach is employed which develops the sensitivity analysis and optimization algorithm in continuous state space, resorting to discretization only for efficient numerical integration of differential equations. A numerical comparison of the state space and conventional nonlinear programming methods is carried out for two test problems, in which the state space method requires only one-tenth the computing time reported for the nonlinear programming approach.
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