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IET Control Theory and Applications • Vol 10 • No 12
Data‐driven policy iteration algorithm for optimal control of continuous‐time Itô stochastic systems with Markovian jumps
May 2016 • Jun Song, Shuping He, Fei Liu, Yugang Niu, Zhengtao Ding
This studies the infinite horizon optimal control problem for a class of continuous‐time systems subjected to multiplicative noises and Markovian jumps by using a data‐driven policy iteration algorithm. The optimal control problem is equivalent to solve a stochastic coupled algebraic Riccatic equation (CARE). An off‐line iteration algorithm is first established to converge the solutions of the stochastic CARE, which is generalised from an implicit iterative algorithm. By applying subsystems transformation (ST) tec…
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