Discrete Time Mean-Field Stochastic Linear-Quadratic Optimal Control Problems
Robert James Elliott, Xun Li, Yuan‐Hua Ni
Abstract
Open-access reader
Robert James Elliott, Xun Li, Yuan‐Hua Ni
Abstract
Open-access reader
This paper first presents necessary and sufficient conditions for the solvability of discrete time, mean-field, stochastic linear-quadratic optimal control problems. Then, by introducing several sequences of bounded linear operators, the problem becomes an operator stochastic LQ problem, in which the optimal control is a linear state feedback. Furthermore, from the form of the optimal control, the problem changes to a matrix dynamic optimization problem. Solving this optimization problem, we obtain the optimal feedback gain and thus the optimal control. Finally, by completing the square, the optimality of the above control is validated.
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This paper first presents necessary and sufficient conditions for the solvability of discrete time, mean-field, stochastic linear-quadratic optimal control problems. Then, by introducing several sequences of bounded linear operators, the problem becomes an operator stochastic LQ problem, in which the optimal control is a linear state feedback. Furthermore, from the form of the optimal control, the problem changes to a matrix dynamic optimization problem. Solving this optimization problem, we obtain the optimal feedback gain and thus the optimal control. Finally, by completing the square, the optimality of the above control is validated.
Key concepts: Optimal control, Stochastic control, Mathematics, Linear-quadratic-Gaussian control, Discrete time and continuous time, Mathematical optimization, Optimization problem, Bounded function