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CLC number: TB12
On-line Access: 2024-08-27
Received: 2023-10-17
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On stochastic optimal control of partially observable nonlinear quasi Hamiltonian systems
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ZHU Wei-qiu, YING Zu-guang. On stochastic optimal control of partially observable nonlinear quasi Hamiltonian systems[J]. Journal of Zhejiang University Science A, 2004, 5(11): 1313-1317.
@article{title="On stochastic optimal control of partially observable nonlinear quasi Hamiltonian systems",
author="ZHU Wei-qiu, YING Zu-guang",
journal="Journal of Zhejiang University Science A",
volume="5",
number="11",
pages="1313-1317",
year="2004",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2004.1313"
}
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%T On stochastic optimal control of partially observable nonlinear quasi Hamiltonian systems
%A ZHU Wei-qiu
%A YING Zu-guang
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%P 1313-1317
%@ 1869-1951
%D 2004
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2004.1313
TY - JOUR
T1 - On stochastic optimal control of partially observable nonlinear quasi Hamiltonian systems
A1 - ZHU Wei-qiu
A1 - YING Zu-guang
J0 - Journal of Zhejiang University Science A
VL - 5
IS - 11
SP - 1313
EP - 1317
%@ 1869-1951
Y1 - 2004
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2004.1313
Abstract: A stochastic optimal control strategy for partially observable nonlinear quasi Hamiltonian systems is proposed. The optimal control forces consist of two parts. The first part is determined by the conditions under which the stochastic optimal control problem of a partially observable nonlinear system is converted into that of a completely observable linear system. The second part is determined by solving the dynamical programming equation derived by applying the stochastic averaging method and stochastic dynamical programming principle to the completely observable linear control system. The response of the optimally controlled quasi Hamiltonian system is predicted by solving the averaged Fokker-Planck-Kolmogorov equation associated with the optimally controlled completely observable linear system and solving the Riccati equation for the estimated error of system states. An example is given to illustrate the procedure and effectiveness of the proposed control strategy.
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