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Embedded optimal control problems
IEEE Conference on Decision and Control and European Control Conference, 2011In this paper we define a class of optimal control problems which we denote “embedded optimal control problems”. These are not true optimal control problems since the control system is not locally controllable on the manifold on which it is defined.
Nikolaj Nordkvist +3 more
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Conversion of optimal control problems into parameter optimization problems
Guidance, Navigation, and Control Conference, 1996Summary: Several methods exist for converting optimal control problems into parameter optimization problems, and they are categorized by the unknowns of the parameter optimization problem, the numerical integration technique, and the order of the integration technique.
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NABSDEs and optimal control problem
2016 3rd International Conference on Systems and Informatics (ICSAI), 2016One innovation of our paper lies in the introduction of neutral anticipated backward stochastic differential equations (NABSDEs). By the theorem of fixed point, we show that those equations have unique solutions. This type of equations can be regarded as an expansion of classical backward stochastic differential equations (BSDEs). On the other hand, we
Shuang Wu, Lan Shu
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Discretization of Optimal Control Problems
2011Solutions to optimization problems with pde constraints inherit special properties; the associated state solves the pde which in the optimization problem takes the role of a equality constraint, and this state together with the associated control solves an optimization problem, i.e., together with multipliers satisfies first- and second-order necessary
Hinze, Michael, Rösch, Arnd
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Optimal Control of Obstacle Problem
Proceedings of the 2019 4th International Conference on Mathematics and Artificial Intelligence, 2019In this paper, we consider an optimal control problem for an elliptic obstacle problem. Using a family of semi-linear elliptic partial differential equations to approximate the obstacle problem, we obtain an approximate optimal problem for partial differential equations. Then, we propose a new method to prove the objective functional in the approximate
Xuan Zheng, Qin Gao
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2019
We consider discrete-time stochastic optimal control problems over a finite number of decision stages in which several controllers share different information and aim at minimizing a common cost functional. This organization can be described within the framework of “team theory.” Unlike the classical optimal control problems, linear-quadratic-Gaussian ...
Riccardo Zoppoli +3 more
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We consider discrete-time stochastic optimal control problems over a finite number of decision stages in which several controllers share different information and aim at minimizing a common cost functional. This organization can be described within the framework of “team theory.” Unlike the classical optimal control problems, linear-quadratic-Gaussian ...
Riccardo Zoppoli +3 more
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Degenerate problems of optimal control. II
Automation and Remote Control, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gurman, V. I., Kang, Ni Ming
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Autonomous optimal control problems
Reports on Mathematical Physics, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On the Synthesis Problem for Optimal Control Systems
SIAM Journal on Control and Optimization, 2000Summary: A new approach to the synthesis problem of optimal controls of feedback type is considered. Algorithms of operating optimal controllers which are able to calculate values of optimal feedbacks during each particular control process in real time are described. The algorithm of operating the controller of the first type (continuous controller) is
R. Gabasov +2 more
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On pseudoparabolic optimal control problems
Kybernetika, 1993This paper discusses the following optimal control problem \[ J(u)= \min_{u\in U_{ad}} J(u)= \min_{u\in U_{ad}} \{\| Dy(T,u)- z_ d\|^ 2_ X+ j(u)\}, \] subject to the pseudoparabolic equations \[ A_ 1(t,u) y_ t(t,u)+ A_ 0(t,u) y(t,u)= f(t),\;A_ 1(0,u) y_ t(0,u)= f_ 0, \] where \(A_ 1(\cdot,\cdot)\), \(A_ 0(\cdot,\cdot)\), \(f(\cdot)\), \(j(\cdot ...
Igor Bock, Ján Lovísek
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