Reliable Control for Stochastic Systems with Low Sensitivity
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In this chapter, the problem of controlling stochastic linear systems with quadratic criterion which includes sensitivity variables is investigated. It is proved that the optimal full state-feedback control law with risk aversion can be realized by the cascade of mathematical statistics of performance uncertainty and a linear feedback. A set of nonlinear matrix equations are obtained, which constitutes the necessary and sufficient conditions that must be satisfied for an optimal solution.
KeywordsPerformance Uncertainty Constant Variance Parameter Performance-measure Statistics Stationary Optimal Control Performance Risk Aversion
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