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Title: Composite Robust $$H_\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

Here in this note, the robust stochastic stabilization and robust H_infinity 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 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.
Authors:
 [1] ;  [2] ;  [3]
  1. Northeastern Univ., Shenyang (China). State Key Lab. of Synthetical Automation for Process Industries
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Beihang Univ., Beijing (China). Key Lab. of Science and Technology on Aircraft Control for National Defence
Publication Date:
Report Number(s):
PNNL-SA-125771
Journal ID: ISSN 0018-9286
Grant/Contract Number:
AC05-76RL01830; 61333007; 61621004; 2015M571322
Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Automatic Control
Additional Journal Information:
Journal Name: IEEE Transactions on Automatic Control; Journal ID: ISSN 0018-9286
Publisher:
IEEE
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE; National Natural Science Foundation of China (NNSFC); Chinese National Post-doctor Science Foundation
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; Robustness; Disturbance observers; Stochastic processes; Control systems; Stochastic systems; Uncertainty; Uncertain systems; Composite control; stochastic systems; linear matrix inequalities; robust control
OSTI Identifier:
1438242

Liu, Yunlong, Wang, Hong, and Guo, Lei. Composite Robust $H_\infty$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer. United States: N. p., Web. doi:10.1109/TAC.2018.2819683.
Liu, Yunlong, Wang, Hong, & Guo, Lei. Composite Robust $H_\infty$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer. United States. doi:10.1109/TAC.2018.2819683.
Liu, Yunlong, Wang, Hong, and Guo, Lei. 2018. "Composite Robust $H_\infty$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer". United States. doi:10.1109/TAC.2018.2819683.
@article{osti_1438242,
title = {Composite Robust $H_\infty$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer},
author = {Liu, Yunlong and Wang, Hong and Guo, Lei},
abstractNote = {Here in this note, the robust stochastic stabilization and robust H_infinity 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 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.},
doi = {10.1109/TAC.2018.2819683},
journal = {IEEE Transactions on Automatic Control},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {3}
}