Value iteration algorithm for continuous-time linear quadratic stochastic optimal control problems  

作　　者：Guangchen WANG Heng ZHANG 

机构地区：[1]School of Control Science and Engineering,Shandong University,Jinan 250061,China

出　　处：《Science China(Information Sciences)》2024年第2期166-176,共11页中国科学（信息科学）（英文版）

基　　金：This work was supported by National Natural Science Foundation of China(Grant Nos.61925306,61821004,11831010);National Key R&D Program of China(Grant No.2022YFA1006103);Natural Science Foundation of Shandong Province(Grant Nos.ZR2019ZD42,ZR2020ZD24).

摘　　要：In this study,we investigate a continuous-time infinite-horizon linear quadratic stochastic optimal control problem with multiplicative noise in control and state variables.Using the techniques of stochastic stability,exact observability,and stochastic approximation,a value iteration algorithm is developed to solve the corresponding generalized algebraic Riccati equation.Unlike the existing policy iteration algorithm,this algorithm does not rely on an initial stabilizing control.Further,this algorithm can also be used to compute policy evaluation steps that arise in the policy iteration algorithm.Herein,a simulation example is provided to validate the obtained results.

关 键 词：stochastic systems optimal control linear quadratic stochastic problem generalized algebraic Riccati equation value iteration algorithm 

分 类 号：O232[理学—运筹学与控制论]