Abstract
In this note, the robust stochastic stabilization and robust H∞ control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with the state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbance rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.
Original language | English |
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Article number | 8325456 |
Pages (from-to) | 4345-4352 |
Number of pages | 8 |
Journal | IEEE Transactions on Automatic Control |
Volume | 63 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2018 |
Externally published | Yes |
Funding
Manuscript received December 13, 2017; accepted March 8, 2018. Date of publication March 26, 2018; date of current version December 3, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61333007 and Grant 61621004, in part by the Chinese National Post-doctor Science Foundation under Grant 2015M571322, and in part by the CCSI of the Pacific Northwest National Laboratory. Recommended by Associate Editor L. Wu. (Corresponding author: Hong Wang.) Y. Liu is with the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China (e-mail: [email protected]).
Funders | Funder number |
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CCSI | |
Pacific Northwest National Laboratory | |
National Natural Science Foundation of China | 61333007, 61621004, 2015M571322 |
Keywords
- Composite control
- linear matrix inequalities
- robust control
- stochastic systems