Implicit iterative algorithms with a tuning parameter for discrete stochastic Lyapunov matrix equations
| Autor: | Ying Zhang, Ai-Guo Wu, Chun-Tao Shao |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Class (set theory) Control and Optimization Iterative method MathematicsofComputing_NUMERICALANALYSIS Monotonic function 02 engineering and technology Multiplicative noise Computer Science Applications Human-Computer Interaction 020901 industrial engineering & automation Exponential stability Control and Systems Engineering Control theory Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Electrical and Electronic Engineering Special case Algorithm Lyapunov matrix Mathematics |
| Zdroj: | IET Control Theory & Applications. 11:1554-1560 |
| ISSN: | 1751-8652 |
| DOI: | 10.1049/iet-cta.2016.1601 |
| Popis: | An implicit iterative algorithm is established for solving a class of Lyapunov matrix equations appearing in the discrete-time stochastic systems with multiplicative noise. This algorithm contains a tuning parameter which can be appropriately chosen such that it has better convergence performance. Some convergence conditions have been derived for the proposed iterative algorithm, and for a special case an approach is given to choose the optimal tuning parameter such that the algorithm has the best convergence performance. In addition, the properties of boundedness and monotonicity of the proposed algorithm are also investigated when the corresponding stochastic system is asymptotically mean-square stable. |
| Databáze: | OpenAIRE |
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