Establishes maximum principle for convex stochastic optimal control of partially and fully coupled FBSΔEs with finite-state uncertainty via adjoint difference equations.
A global stochastic maximum principle for fully coupled forward-backward stochastic systems
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abstract
We study a stochastic optimal control problem for fully coupled forward-backward stochastic control systems with a nonempty control domain. For our problem, the first-order and second-order variational equations are fully coupled linear FBSDEs. Inspired by Hu (Hu, Probability, Uncertainty and Quantitative Risk, 2(1) (2017):pp 1-20), we develop a new decoupling approach by introducing an adjoint equation which is a quadratic BSDE. By revealing the relations among the terms of the first-order Taylor's expansions, we estimate the orders of them and derive a global stochastic maximum principle which includes a completely new term. Applications to stochastic linear quadratic control problems are investigated.
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math.OC 1years
2019 1verdicts
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Maximum principle for stochastic optimal control problem of finite state forward-backward stochastic difference systems
Establishes maximum principle for convex stochastic optimal control of partially and fully coupled FBSΔEs with finite-state uncertainty via adjoint difference equations.