Optimal tracking control for stochastic discrete-time systems based on improved Riccati iterative algorithm
Author:
Affiliation:
1. School of Science, Shenyang Jianzhu University,Shenyang,P. R. China,110168
2. School of Electrical and Control Engineering, Shenyang Jianzhu University,,Shenyang,P. R. China,110168
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9901509/9901494/09902035.pdf?arnumber=9902035
Reference14 articles.
1. Iterative methods for a linearly perturbed algebraic matrix Riccati equation arising in stochastic control;chun;Numerical Functional Analysis and Optimization,2013
2. New iterative algorithms for solving coupled Markovian jump Lyapunov equations;wu;IEEE Transactions Automatic Control,2015
3. Neural-network-based stochastic linear quadratic optimal tracking control scheme for unknown discrete-time systems using adaptive dynamic programming
4. Stochastic linear quadratic optimal control for model-free discrete-time systems based on Q-learning algorithm
5. Two iterative algorithms for stochastic algebraic Riccati matrix equations
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1. An improved iterative algorithm for solving optimal tracking control problems of stochastic systems;Mathematics and Computers in Simulation;2023-11
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