Results 241 to 250 of about 896,969 (285)
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1987
In the long history of mathematics, stochastic optimal control is a rather recent development. Using Bellman’s Principle of Optimality along with measure-theoretic and functional-analytic methods, several mathematicians such as H. Kushner, W. Fleming, R. Rishel. W.M. Wonham and J.M.
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In the long history of mathematics, stochastic optimal control is a rather recent development. Using Bellman’s Principle of Optimality along with measure-theoretic and functional-analytic methods, several mathematicians such as H. Kushner, W. Fleming, R. Rishel. W.M. Wonham and J.M.
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Controllability of Stochastic Game-Based Control Systems
SIAM Journal on Control and Optimization, 2019The main results of this paper are the following. First, it formulates the general stochastic game-based control systems (GBCSs) ``as a two-level hierarchical structure, where the lower level is a noncooperative stochastic differential game among multiple agents, and the higher level is a macroregulator which can intervene in the lower level ...
Ren-Ren Zhang, Lei Guo 0001
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Singular perturbations in stochastic control
IFAC Proceedings Volumes, 1984We consider a class of problems in stochastic control theory involving stochastic systems with small parameters. Using both analytical and probabilistic methods adapted to the special structures of singularly perturbed stochastic control problems, we develop a systematic methodology for their analysis.
Bensoussan, Alain, Blankenship, G.L.
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Stochastic Control with Imperfect Models
SIAM Journal on Control and Optimization, 2008We consider the problem of worst case performance estimation for a stochastic dynamic model in the presence of model uncertainty. This is cast as a nonclassical controlled diffusion problem. An infinite dimensional linear programming formulation is given and its dual is derived.
Arnab Basu, Vivek S. Borkar
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Advances in stochastic distribution control
2008 10th International Conference on Control, Automation, Robotics and Vision, 2008Stochastic distribution control systems aims at the controller design so as to realize a shape control of the distributions of certain random variables in the process. Once the probability density functions (PDFs) of these variables are used to describe their distributions, the control task is to obtain control signals so that the output PFDs of the ...
Aiping Wang +2 more
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Stochastic controllability and stochastic Lyapunov functions
Proceedings of the 27th IEEE Conference on Decision and Control, 2003Sufficient conditions are established under which the law of large numbers and related ergodic theorems hold for nonlinear stochastic systems operating under feedback. It is shown that these conditions hold whenever a moment condition is satisfied, which may be interpreted as a generalization of the martingale property.
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Stochastic Realization for Stochastic Control with Partial Observations
2007The purpose of this paper is to present a novel way to formulate control problems with partial observations of stochastic systems. Themethod is based on stochastic realization theory.
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Nonlinear Compensation and Stochastic Control
1988 American Control Conference, 1988The usual ARMAX linear model for a discrete-time system is generalized to include a nonlinear characteristic. A nonlinear compensation scheme is proposed which enables a modified LQG control approach to be applied to the precompensated system. The solution is relatively simple and if the plant matches the modelled situation asymptotic stability is ...
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Pathwise Stochastic Optimal Control
SIAM Journal on Control and Optimization, 2007This paper approaches optimal control problems for discrete-time controlled Markov processes by representing the value of the problem in a dual Lagrangian form; the value is expressed as an infimum over a family of Lagrangian martingales of an expectation of a pathwise supremum of the objective adjusted by the Lagrangian martingale term.
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