0000000000128917

AUTHOR

Zhaojing Wu

showing 5 related works from this author

Dissipativity-Based Small-Gain Theorems for Stochastic Network Systems

2016

In this paper, some small-gain theorems are proposed for stochastic network systems which describe large-scale systems with interconnections, uncertainties and random disturbances. By the aid of conditional dissipativity and showing times of stochastic interval, small-gain conditions proposed for the deterministic case are extended to the stochastic case. When some design parameters are tunable in practice, we invaginate a simpler method to verify small-gain condition by selecting one subsystem as a monitor. Compared with the existing results, the existence-and-uniqueness of solution and ultimate uniform boundedness of input are removed from requirements of input-to-state stability and smal…

0209 industrial biotechnologystochastic systemsComputer Science Applications1707 Computer Vision and Pattern Recognition02 engineering and technologyInterval (mathematics)Stability (probability)Electronic mailComputer Science Applicationsinput-to-state stabilityDissipativity; input-to-state stability; network systems; stochastic systems; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic EngineeringNonlinear system020901 industrial engineering & automationnetwork systemsControl and Systems EngineeringControl theoryControl system0202 electrical engineering electronic engineering information engineeringUniform boundedness020201 artificial intelligence & image processingStochastic optimizationElectrical and Electronic EngineeringDissipativityMathematicsIEEE Transactions on Automatic Control
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On stability and dissipativity of stochastic nonlinear systems

2012

Input-to-state stability of nonlinear control system is described in several different manners, and has been a central concept since the equivalences among them were verified. In this paper, a framework of stability and dissipativity for stochastic control systems is constructed on the maximal existence interval of behaviors (states and external inputs), by the aid of stochastic Barbalat lemma and stochastic dissipativity. The main work consists of three aspects. First, input-to-state stability and robust stability are extended to the stochastic case, and several criteria are established. Second, two forms of dissipativity and their criteria are presented. Third, the key relations among the…

Stochastic controlNonlinear systemWork (thermodynamics)Lemma (mathematics)Control theoryStability (learning theory)Interval (mathematics)Nonlinear controlLipschitz continuityMathematics2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
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Stability of stochastic nonlinear systems with state-dependent switching

2013

In this paper, the problem of stability on stochastic systems with state-dependent switching is investigated. To analyze properties of the switched system by means of Itô’s formula and Dynkin’s formula, it is critical to show switching instants being stopping times. When the given active-region set can be replaced by its interior, the local solution of the switched system is constructed by defining a series of stopping times as switching instants, and the criteria on global existence and stability of solution are presented by Lyapunov approach. For the case where the active-region set can not be replaced by its interior, the switched systems do not necessarily have solutions, thereby quasi-…

stochastic systemsStability (learning theory)Mathematical proofnonlinear control systemsSet (abstract data type)State-dependent switching; Stochastic systems; Switched systems; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic EngineeringExponential stabilityControl theoryElectrical and Electronic EngineeringSwitched systemsMathematicsLyapunov methodsStochastic systemsSeries (mathematics)Stochastic processApplied MathematicsComputer Science Applications1707 Computer Vision and Pattern Recognitionstate-dependent switchingstabilityComputer Science ApplicationsNonlinear systemControl and Systems EngineeringState dependentswitched systemscontrol system synthesisState-dependent switching
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Small-gain conditions for stochastic network systems

2013

In this paper, some small-gain conditions are presented for stochastic network systems which can describe many large-scale systems with interconnections, nonlinear behaviors, uncertainties and random disturbances. One subsystem is selected as monitor with the requirement that the gains to other systems are smooth concave functions. The relations of members under the supervise of the monitor are described as bilateral plus multilateral relations of gains. For the deterministic case, the requirement on the monitor can be removed. To demonstrate the power of this result, the small-gain conditions cover interconnected system with two subsystems as a special case. Compared with the existing resu…

Nonlinear systemMathematical optimizationCover (topology)Concave functionControl theoryStochastic processUniform boundednessSpecial caseStability (probability)Power (physics)Mathematics52nd IEEE Conference on Decision and Control
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Disturbance observer-based disturbance attenuation control for a class of stochastic systems

2016

This paper studies a class of stochastic systems with multiple disturbances which include the disturbance with partially-known information and the white noise. A disturbance observer is constructed to estimate the disturbance with partially-known information, based on which, a disturbance observer-based disturbance attenuation control (DOBDAC) scheme is proposed by combining pole placement and linear matrix inequality (LMI) methods.

0209 industrial biotechnologyDisturbance (geology)Computer scienceAttenuation020208 electrical & electronic engineeringControl (management)Disturbance observer-based disturbance attenuation controlStochastic systemLinear matrix inequalityDisturbance observer-based disturbance attenuation control; Multiple disturbances; Stochastic system; Control and Systems Engineering; Electrical and Electronic Engineering02 engineering and technologyWhite noiseClass (biology)020901 industrial engineering & automationControl and Systems EngineeringControl theoryFull state feedbackDisturbance observer0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringMultiple disturbancesAutomatica
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