0000000000684540

AUTHOR

Rongni Yang

showing 4 related works from this author

Induced ℓ<inf>2</inf> control of discrete-time Takagi-Sugeno fuzzy systems with time-varying delays via dynamic output feedback

2012

This paper is concerned with analyzing a novel model transformation of discrete-time Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and applying it to dynamic output feedback (DOF) controller design. A new auxiliary model is proposed by employing a new approximation for time-varying delay state, and then delay partitioning method is used to analyze the scaled small gain of this auxiliary model. A sufficient condition on discrete-time T-S fuzzy systems with time-varying delays, which guarantees the corresponding closed-loop system to be asymptotically stable and has an induced l 2 disturbance attenuation performance, is derived by employing the scaled small gain theorem. Then the…

Set (abstract data type)Small-gain theoremDiscrete time and continuous timeControl theoryStability theoryModel transformationFuzzy control systemState (functional analysis)computercomputer.programming_languageMathematics2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
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Predictive control of networked systems with communication delays

2012

This paper studies the problem of predictive output feedback control for networked control systems with random communication delays. A networked predictive control scheme is employed to compensate for random communication delays, which mainly consists of the control prediction generator and network delay compensator. Furthermore, a new strategy of designing the time-varying predictive controller with mixed random delays for networked systems is proposed. Then the system can be formulated as a Markovian jump system. New techniques are presented to deal with the distributed delay in the discrete-time domain. Based on analysis of closed-loop networked predictive control systems, the designed p…

symbols.namesakeModel predictive controlComputer scienceControl theoryControl systemNetwork delaysymbolsMarkov processControl engineeringNetworked control systemData lossStability (probability)2012 IEEE International Symposium on Intelligent Control
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Mathematical Modeling, Analysis, and Advanced Control of Complex Dynamical Systems

2014

1 School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia 2 Department of Engineering, Faculty of Technology and Science, University of Agder, 4898 Grimstad, Norway 3 College of Automation, Chongqing University, Chongqing 400044, China 4 School of Control Science and Engineering, Shandong University, Jinan 250061, China 5 College of Automation, Harbin Engineering University, Harbin 150001, China

Article SubjectDynamical systems theorybusiness.industryComputer sciencelcsh:MathematicsGeneral MathematicsVDP::Technology: 500::Mechanical engineering: 570Control (management)General Engineeringlcsh:QA1-939AutomationEngineering managementEngineering (all)lcsh:TA1-2040Mathematics (all)Applied mathematicslcsh:Engineering (General). Civil engineering (General)ChinabusinessMathematics (all); Engineering (all)Mathematical Problems in Engineering
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Full- and reduced-order filter design for discrete-time T-S fuzzy systems with time-varying delay

2012

This paper is focused on the problem of ℋ ∞ filtering for a class of discrete-time T-S fuzzy time-varying delay systems. Our interest is how to design full- and reduced-order filters that guarantee the filtering error system to be asymptotically stable with a prescribed ℋ ∞ performance. Sufficient conditions for the obtained filtering error system are proposed by applying an input-output approach and a two-term approximation method, which is employed to approximate the time-varying delay. The corresponding full and reduced-order filter design is cast into a convex optimization problem, which can be efficiently solved by standard numerical algorithms.

Filter designDiscrete time and continuous timeControl theoryStability theoryConvex optimizationKalman filterFuzzy control systemFuzzy logicReduced orderMathematics2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
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