Optimal Performance Control of Stochastic Dynamical Systems

نویسنده

  • J. Li
چکیده

A family of performance control policies of stochastic dynamic systems are proposed based on the probability density evolution theory and numerical optimizing strategies in the present paper. Firstly, the general form of the control policies of stochastic optimal control systems is raised according to the classical optimal control theory of linear quadratic regulator (LQR). Then, three classes of optimal control norms with objective performance indices are developed at hierarchical levels from the mean sub-norm, the mean-standard deviation sub-norm to the exceedance probability sub-norm. A linear single-degree-of-freedom system subjected to random ground motions is investigated for the illustrative purpose. The results show that the effectiveness of responses control hinges on the physical meanings of the optimal control norms. The multi-penalty norm, e. g., the accelerationand input force constrained displacement controlled norm, in the objective performance norms behaves more comprehensively than the single-penalty norm and non-penalty norm that is the prime norm to the structural single-objective control. Among the three sub-norms the exceedance probability sub-norm is the most reasonable.

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تاریخ انتشار 2008