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• W2113151258 abstract "This paper considers a new class of discrete time stochastic uncertain systems in which the uncertainty is described by a constraint on the relative entropy between a nominal noise distribution and the perturbed noise distribution. This uncertainty description is a natural extension to the case of stochastic uncertain systems, of the sum quadratic constraint uncertainty description. This paper solves problems of worst-case robust performance analysis and output feedback minimax optimal controller synthesis in a general nonlinear setting. Specializing these results to the linear case leads to a minimax linear quadratic Gaussian (LQG) optimal controller. This controller is defined by Riccati difference equations and a Kalman filter-like state equation. The paper also shows that the minimax LQG problem will have a solution if and only if a corresponding H/sup /spl infin// control problem has a solution. A linear example is presented to illustrate the minimax LQG methodology." @default.
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• W2113151258 date "2000-03-01" @default.
• W2113151258 modified "2023-09-26" @default.
• W2113151258 title "Minimax optimal control of stochastic uncertain systems with relative entropy constraints" @default.
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• W2113151258 doi "https://doi.org/10.1109/9.847720" @default.
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