Results 231 to 240 of about 265,042 (255)
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IFAC Proceedings Volumes, 1987
Abstract The principal techniques used up to now for the analysis of stochastic adaptive control systems have been (i) super-martingale (often called stochastic Lyapunov) methods and (ii) methods relying upon the strong consistency of some parameter estimation scheme. Optimal stochastic control and filtering methods have also been employed.
P.E. Caines, S.P. Meyn, A. Aloneftis
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Abstract The principal techniques used up to now for the analysis of stochastic adaptive control systems have been (i) super-martingale (often called stochastic Lyapunov) methods and (ii) methods relying upon the strong consistency of some parameter estimation scheme. Optimal stochastic control and filtering methods have also been employed.
P.E. Caines, S.P. Meyn, A. Aloneftis
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Proceedings of the 1972 IEEE Conference on Decision and Control and 11th Symposium on Adaptive Processes, 1972
The feedback stochastic decision rule is developed for potential buffer stock agencies in cocoa. This rule prescribes the values of policy variables as a linear function of actually observed endogenous variables with time-varying coefficients which reflect the social welfare and is derived by, first, solving the deterministic non-linear optimization ...
Han Kim, Louis Goreux, David Kendrick
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The feedback stochastic decision rule is developed for potential buffer stock agencies in cocoa. This rule prescribes the values of policy variables as a linear function of actually observed endogenous variables with time-varying coefficients which reflect the social welfare and is derived by, first, solving the deterministic non-linear optimization ...
Han Kim, Louis Goreux, David Kendrick
openaire +1 more source
Four unsolved problems in stability and optimal control theory of stochastic systems
Academia Letters, 2021openaire +1 more source
A Contraction Theory Approach to Stochastic Incremental Stability
IEEE Transactions on Automatic Control, 2009Quang-Cuong Pham +2 more
exaly