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Stochastic minimax optimal control strategy for uncertain quasi-Hamiltonian systems using stochastic maximum principle.
- Source :
- Structural & Multidisciplinary Optimization; Jan2014, Vol. 49 Issue 1, p69-80, 12p
- Publication Year :
- 2014
-
Abstract
- A stochastic minimax optimal control strategy for uncertain quasi-Hamiltonian systems is proposed based on the stochastic averaging method, stochastic maximum principle and stochastic differential game theory. First, the partially completed averaged Itô stochastic differential equations are derived from a given system by using the stochastic averaging method for quasi-Hamiltonian systems with uncertain parameters. Then, the stochastic Hamiltonian system for minimax optimal control with a given performance index is established based on the stochastic maximum principle. The worst disturbances are determined by minimizing the Hamiltonian function, and the worst-case optimal controls are obtained by maximizing the minimal Hamiltonian function. The differential equation for adjoint process as a function of system energy is derived from the adjoint equation by using the Itô differential rule. Finally, two examples of controlled uncertain quasi-Hamiltonian systems are worked out to illustrate the application and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1615147X
- Volume :
- 49
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Structural & Multidisciplinary Optimization
- Publication Type :
- Academic Journal
- Accession number :
- 93449004
- Full Text :
- https://doi.org/10.1007/s00158-013-0958-x