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Mean-Square Stability and Stabilizability Analyses of LTI Systems Under Spatially Correlated Multiplicative Perturbations [article]

Jianqi Chen and Tian Qi and Jie Chen
2022 arXiv   pre-print
In this paper, we investigate the mean-square stability and stabilizability problems for linear time-invariant systems under stochastic spatially correlated multiplicative uncertainties.  ...  Theorem 2 provides a complete solution to the mean-square stabilizability problem in the first-order case against the multiplicative and divisive stochastic uncertainties simultaneously.  ...  We first develop a mean-square stability condition, namely a generalized mean-square small gain theorem capable of coping with correlated stochastic uncertainties.  ... 
arXiv:2112.05363v2 fatcat:z6ltuuzi7bepvoayiuusugzmzq

2019 Index IEEE Transactions on Automatic Control Vol. 64

2019 IEEE Transactions on Automatic Control  
., +, TAC Aug. 2019 3391-3398 Mean Square Stabilization Over SNR-Constrained Channels With Colored and Spatially Correlated Additive Noises.  ...  ., +, TAC May 2019 1874-1889 Mean Square Stabilization Over SNR-Constrained Channels With Colored and Spatially Correlated Additive Noises.  ... 
doi:10.1109/tac.2020.2967132 fatcat:o2hd2t4jz5fbpkcemjt5aj7xrm

Linear Matrix Inequalities for an Iterative Solution of Robust Output Feedback Control of Systems with Bounded and Stochastic Uncertainty

Andreas Rauh, Swantje Romig
2021 Sensors  
with the help of LMIs so that their error dynamics become insensitive against stochastic noise.  ...  In addition to bounded parameter uncertainty, included in the LMI-based design by means of polytopic uncertainty representations, the recent work of the authors showed that state observers can be optimized  ...  for fractional-order systems with uncertainty [13] [14] [15] [16] .  ... 
doi:10.3390/s21093285 pmid:34068593 fatcat:fan62icuqrfrrghqcvwnmnejrm

2018 Index IEEE Transactions on Automatic Control Vol. 63

2018 IEEE Transactions on Automatic Control  
Mean Square Stability Analysis of Stochastic Continuous-Time Linear Networked Systems.  ...  ., +, TAC Jan. 2018 37-52 Mean Square Stability Analysis of Stochastic Continuous-Time Linear Networked Systems.  ... 
doi:10.1109/tac.2019.2896796 fatcat:bwmqasulnzbwhin5hv4547ypfe

2020 Index IEEE Transactions on Automatic Control Vol. 65

2020 IEEE Transactions on Automatic Control  
., +, TAC March 2020 941-954 Correlation An Input-Output Approach to Structured Stochastic Uncertainty.  ...  ., +, TAC Dec. 2020 5043-5057 Mean-Square Exponential Stability for Stochastic Control Systems With Discrete-Time State Feedbacks and Their Numerical Schemes in Simula- tion.  ... 
doi:10.1109/tac.2020.3046985 fatcat:hfiqhyr7sffqtewdmcwzsrugva

Managing interference for stabilization over wireless channels

Ibrahim Bilal, Ali A. Zaidi, Tobias J. Oechtering, Mikael Skoglund
2012 2012 IEEE International Symposium on Intelligent Control  
By employing these schemes, we derive sufficient conditions for mean square stability.  ...  This thesis in particular focuses on such a problem; it aims to improve stabilizability of linear systems by managing interference in the wireless channels.  ...  Note that the system is stabilizable even if A is unstable. We introduce the concept of mean square stability [21] . Definition 1.1.  ... 
doi:10.1109/isic.2012.6398272 dblp:conf/IEEEisic/BilalZOS12 fatcat:qkf5admypnavvfttvqk65xx24y

Integrated predictive power control and dynamic channel assignment in mobile radio systems

K. Shoarinejad, J.L. Speyer, G.J. Pottie
2003 IEEE Transactions on Wireless Communications  
His general area of interest is in applying stochastic analysis, estimation and filtering, and other system theoretic techniques to applications in communication, control, and navigation systems. with  ...  he was a Teaching and Research Assistant in the Electrical Engineering Department at UCLA where he was involved in research on stochastic decentralized systems with applications in communications and control  ...  Also in [10] , stochastic measurements were incorporated in the power control algorithm and it was shown that the power levels converge, in the mean square sense, to the optimal power levels.  ... 
doi:10.1109/twc.2003.817418 fatcat:vpe6udxti5gcph6rec2bbl4diu

An Opportunistic Sensor Scheduling Solution to Remote State Estimation Over Multiple Channels

Duo Han, Yilin Mo, Junfeng Wu, Ling Shi
2016 IEEE Transactions on Signal Processing  
We present a minimum mean square error (MMSE) estimator in a closed-form under the proposed opportunistic sensor schedule.  ...  We consider a sensor scheduling problem where the sensors have multiple choices of communication channel to send their local measurements to a remote state estimator for state estimation.  ...  One can regard the enlarged measurement error covariance β −1 i as a measure of uncertainty introduced by stochastically discretizing the innovation.  ... 
doi:10.1109/tsp.2016.2576421 fatcat:p5n4r4dgqvbhdhhhkjjgcgne5e

The Two-State Implicit Filter Recursive Estimation for Mobile Robots

Michael Bloesch, Michael Burri, Hannes Sommer, Roland Siegwart, Marco Hutter
2018 IEEE Robotics and Automation Letters  
This paper deals with recursive filtering for dynamic systems where an explicit process model is not easily devisable.  ...  The applicability of the proposed approach is experimentally confirmed on two different real mobile robotic state estimation problems.  ...  Consequently, future work will include implementation related topics such as automatic measurement handling, numerical stability, observability constraints, or square root forms.  ... 
doi:10.1109/lra.2017.2776340 dblp:journals/ral/BloeschBSSH18 fatcat:p7olrefqxjdr7i4pt62qdzfb7u

An outlook on robust model predictive control algorithms: Reflections on performance and computational aspects

M. Bahadır Saltık, Leyla Özkan, Jobert H.A. Ludlage, Siep Weiland, Paul M.J. Van den Hof
2018 Journal of Process Control  
Robustness notions with respect to both deterministic (or set based) and stochastic uncertainties are discussed and contributions are reviewed in the model predictive control literature.  ...  In this paper, we discuss the model predictive control algorithms that are tailored for uncertain systems.  ...  We assume that the uncertain and the nominal systems and nom are stabilizable and observable, see [27] for the definitions of stabilizability and observability.  ... 
doi:10.1016/j.jprocont.2017.10.006 fatcat:jg4guutgvzanrdnq5g4qeuosgi

Analysis of delays in networked flight simulators

M.B. Menhaj, M.T. Hagan
1994 IEEE Transactions on Systems, Man and Cybernetics  
The Effect of 'tz on Mean Square Error for a Figure 6 .Figure 6 . 66 6b. The Effect Of 't 2 On Mean Square 6c. The Effect Of 't 2 On Mean Square Figure 6.6d.  ...  Therefore, we need to show that all the eigenvalues of A 7 have negative real parts in order to prove the stabilizability of the system (B-1).  ... 
doi:10.1109/21.293506 fatcat:xrgwpb2ivvefflehyblnm47r24

Theory, algorithms and technology in the design of control systems

Ruth Bars, Patrizio Colaneri, Carlos E. de Souza, Luc Dugard, Frank Allgöwer, Anatolii Kleimenov, Carsten Scherer
2006 Annual Reviews in Control  
Control theory deals with disciplines and methods leading to an automatic decision process in order to improve the performance of a control system.  ...  Distributed hybrid control systems involving extremely large number of interacting control loops, coordinating large number of autonomous agents, handling very large model uncertainties will be in the  ...  agents, to control non-linear, hybrid and stochastic systems and to handle very large model uncertainties.  ... 
doi:10.1016/j.arcontrol.2006.01.006 fatcat:c6jcpbixwvc63hch4hi5pnrxx4

THEORY, ALGORITHMS AND TECHNOLOGY IN THE DESIGN OF CONTROL SYSTEMS

Ruth Bars, Patrizio Colaneri, Carlos E. de Souza, Frank Allgöwer, Anatolii Kleimenov, Carsten Scherer
2005 IFAC Proceedings Volumes  
Control theory deals with disciplines and methods leading to an automatic decision process in order to improve the performance of a control system.  ...  Distributed hybrid control systems involving extremely large number of interacting control loops, coordinating large number of autonomous agents, handling very large model uncertainties will be in the  ...  agents, to control non-linear, hybrid and stochastic systems and to handle very large model uncertainties.  ... 
doi:10.3182/20050703-6-cz-1902.00422 fatcat:3h4fskpt7fan3mbzk5bd4e4que

4 Some Control-Theoretic Examples [chapter]

2018 The Control Systems Handbook  
A well-known fact for stochastic systems is that the mean squared value of the outputs can be computed by solving the appropriate Lyapunov equation [4] .  ...  ., Mean square stability criteria for stochastic feedback systems. Int. J. Syst. Sci., 4(4), 545-564, 1973. . Z. J. Wu, X. J. Xie, and S. Y.  ...  Stability Robustness to Unstructured Uncertainty for Linear Time Invariant Systems 9-31 12-24 Control System Advanced Methods Linear Quadratic Regulator Control 17-25 Analogously, F ∞ is the full-state  ... 
doi:10.1201/b10384-147 fatcat:m3bdoincxraurlrxxaw4xez37m

Particle filtering with applications in networked systems: a survey

Wenshuo Li, Zidong Wang, Yuan Yuan, Lei Guo
2016 Complex & Intelligent Systems  
We first provide an overview of the particle filtering methods as well as networked systems, and then investigate the recent progress in B Zidong Wang  ...  and implementation of particle filtering algorithms.  ...  The work of W. Li, Y. Yuan and L. Guo  ... 
doi:10.1007/s40747-016-0028-2 fatcat:fj6xjuaenfa3riys43mgvdgiye
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