Results 51 to 60 of about 517,257 (186)

Diffusion Approximation and Optimal Stochastic Control [PDF]

Theory of Probability & Its Applications, 2000
By the same goal with the previous paper of these authors [SIAM J. Control Optimization 34, No. 1, 161-178 (1996; Zbl 0867.93085)] but considering the case of a stochastic control model admitted a diffusion approximation, they show in the present paper that an optimal Lipschitz feedback control of the limit model \[ dX_t = [A_0 (t,X_t)+ a_1 (t,X_t)u_t]
Liptser, R., Runggaldier, W. J., Taksar, M.   +2 more
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Stochastic optimal control via Bellman's principle [PDF]

Automatica, 2003
Consider a stochastic nonlinear controlled continuous-time system with the dynamics \(x(t)\) given by the equation \[ dx(t)=m(x(t),u(t))+ \sigma(x(t),u(t))dB(t),\quad t\in[0,T], \] where \(dB(t)\) is an \(m\)-dimensional standard Brownian motion, \(u(t)\in \mathbb R^m\) is a control at time \(t\), the functions \(m(x,u)\) and \(\sigma(x,u)\) are ...
Crespo, Luis G., Sun, Jian-Qiao
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Stochastic Control for Intra-Region Probability Maximization of Multi-Machine Power Systems Based on the Quasi-Generalized Hamiltonian Theory

Energies, 2019
With the penetration of renewable generation, electric vehicles and other random factors in power systems, the stochastic disturbances are increasing significantly, which are necessary to be handled for guarantying the security of systems.
Xue Lin, Lixia Sun, Ping Ju, Hongyu Li
doaj   +1 more source

Optimal Control Algorithm for Stochastic Systems with Parameter Drift

Sensors, 2023
A novel optimal control problem is considered for multiple input multiple output (MIMO) stochastic systems with mixed parameter drift, external disturbance and observation noise.
Xiaoyan Zhang, Song Gao, Chaobo Chen, Jiaoru Huang   +3 more
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Domain decomposition for stochastic optimal control [PDF]

53rd IEEE Conference on Decision and Control, 2014
This work proposes a method for solving linear stochastic optimal control (SOC) problems using sum of squares and semidefinite programming. Previous work had used polynomial optimization to approximate the value function, requiring a high polynomial degree to capture local phenomena.
Horowitz, Matanya B., Papusha, Ivan, Burdick, Joel W.   +2 more
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Infinite Horizon Optimal Control of Stochastic Delay Evolution Equations in Hilbert Spaces

Abstract and Applied Analysis, 2013
The aim of the present paper is to study an infinite horizon optimal control problem in which the controlled state dynamics is governed by a stochastic delay evolution equation in Hilbert spaces.
Xueping Zhu, Jianjun Zhou
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Stochastic recursive optimal control problem with obstacle constraint involving diffusion type control

Advances in Difference Equations, 2020
This paper concerns a kind of stochastic optimal control problem with recursive utility described by a reflected backward stochastic differential equation (RBSDE, for short) involving diffusion type control which covers regular control problem, singular ...
Zhenda Xu
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Control Theory and Economic Policy Optimization: The Origin, Achievements and the Fading Optimism from a Historical Standpoint [PDF]

International Journal of Business and Development Studies, 2015
Economists were interested in economic stabilization policies as early as the 1930’s but the formal applications of stability theory from the classical control theory to economic analysis appeared in the early 1950’s when a number of control engineers ...
Masoud Derakhshan
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Stochastic Control of Optimized Certainty Equivalents

SIAM Journal on Financial Mathematics, 2022
Optimized certainty equivalents (OCEs) is a family of risk measures widely used by both practitioners and academics. This is mostly due to its tractability and the fact that it encompasses important examples, including entropic risk measures and average value at risk.
Julio Backhoff Veraguas, A. Max Reppen, Ludovic Tangpi   +2 more
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Inverse stochastic optimal controls

Automatica, 2023
We study an inverse problem of the stochastic optimal control of general diffusions with performance index having the quadratic penalty term of the control process. Under mild conditions on the system dynamics, the cost functions, and the optimal control process, we show that our inverse problem is well-posed using a stochastic maximum principle. Then,
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