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An Inverse Stochastic Optimal Control Problem
Proceedings of the 12th International Conference on “Electronics, Communications and Computing", 2022The problem of controlling a compound Poisson process until it leaves an interval is considered. In this paper, instead of choosing the density function of the jumps and trying to find the corresponding value function, from which the optimal control follows at once, we consider the inverse problem: we fix the value of the value function and we look for
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Stochastic optimal control of annuity contracts
Insurance: Mathematics and Economics, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Devolder, Pierre +2 more
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Optimal Stochastic SD Control With Preview
IEEE Transactions on Automatic Control, 2007The problem of H2-optimal sampled-data (SD) preview control is considered. It is assumed that a stochastic reference signal corrupted with additive colored noise acts upon the system so that future values of this input are known within a preview window tau .
Konstantin Yu. Polyakov +2 more
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2018
We consider We consider a probability space \(\Omega ,\mathcal {A},P\) equipped with a filtration \(\mathcal {F}^{t}\) and a standard \(P,\mathcal {F}^{t}\) Wiener process with values in R k .
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We consider We consider a probability space \(\Omega ,\mathcal {A},P\) equipped with a filtration \(\mathcal {F}^{t}\) and a standard \(P,\mathcal {F}^{t}\) Wiener process with values in R k .
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Stochastic Optimal Control Subject to Ambiguity
IFAC Proceedings Volumes, 2011The aim of this paper is to address optimality of control strategies for stochastic control systems subject to uncertainty and ambiguity. Uncertainty corresponds to the case when the true dynamics and the nominal dynamics are dierent but they are dened on the same state space.
Charalambous, Charalambos D. +5 more
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1970
H. J. Kushner has obtained the differential equation satisfied by the optimal feedback control law for a stochastic control system in which the plant dynamics and observations are perturbed by independent additive Gaussian white noise processes.
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H. J. Kushner has obtained the differential equation satisfied by the optimal feedback control law for a stochastic control system in which the plant dynamics and observations are perturbed by independent additive Gaussian white noise processes.
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IEEE Transactions on Automatic Control, 1969
It is shown that, for a class of stochastic systems, i.e., those in which the cost increases as the distance between the stochastic and the deterministic controls increases, the optimal stochastic control is the conditional expectation of the deterministic control, given the measurement history.
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It is shown that, for a class of stochastic systems, i.e., those in which the cost increases as the distance between the stochastic and the deterministic controls increases, the optimal stochastic control is the conditional expectation of the deterministic control, given the measurement history.
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An Approximation Method in Optimal Stochastic Control
SIAM Journal on Control and Optimization, 1978The purpose of this paper is to prove that an approximation scheme can be defined for the general problems of optimal stochastic control which we have solved in Theorie probabiliste du controle des diffusions, Mem. Amer. Math. Soc., 1976 [2].
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Realization of an optimal stochastic control system
IFAC Proceedings Volumes, 1964Abstract : An attempt will be made to apply an optimal stochastic control policy to a realistically flavored dynamical system differing to some extent from the system assumed in the development of the policy. The justification for this will rest on the quality of performance of the resulting system. This paper is a preliminary report on a study of this
R.F. Drenick, R.A. Reiss
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1971
So far we have applied the Kalman filter to systems which were subjected to random disturbances but were not controlled. Very briefly we turn now our attention to the case were we wish to employ measurements to control a system in some optimal manner. Only the simplest problem will be discussed here.
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So far we have applied the Kalman filter to systems which were subjected to random disturbances but were not controlled. Very briefly we turn now our attention to the case were we wish to employ measurements to control a system in some optimal manner. Only the simplest problem will be discussed here.
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