His primary areas of investigation include Control theory, Linear matrix inequality, Control theory, Discrete time and continuous time and Positive systems. His work on Nonlinear system as part of general Control theory research is frequently linked to Whole systems, thereby connecting diverse disciplines of science. His research investigates the connection between Linear matrix inequality and topics such as Robust control that intersect with problems in Delay dependent.
The study incorporates disciplines such as Matrix decomposition, Observer, Markov chain, Time reversibility and Hidden Markov model in addition to Control theory. His Positive systems research integrates issues from Control system, Iterative method and Interval. His Upper and lower bounds research includes themes of State, Exponential stability and Exponential function.
Zhan Shu mainly focuses on Control theory, Control theory, Linear system, Linear matrix inequality and Exponential stability. His Control theory research incorporates elements of Matrix and Iterative method. His studies deal with areas such as State, State, Asynchronous communication and Hidden Markov model as well as Control theory.
The concepts of his Linear system study are interwoven with issues in Control engineering, Bounded function, Mathematical optimization, Linear matrix and Symmetric matrix. His Linear matrix inequality research incorporates themes from Time complexity, Linearization and Robust control. His Exponential stability research includes elements of Lyapunov function, Class, Applied mathematics, Exponential function and Upper and lower bounds.
Zhan Shu spends much of his time researching Control theory, Control theory, Linear system, Lyapunov function and Multi-agent system. Zhan Shu combines subjects such as Transmission Control Protocol, Network packet and Exponential function with his study of Control theory. His Control theory study combines topics in areas such as Exponential stability, Asynchronous communication and Hidden Markov model.
His research in Hidden Markov model intersects with topics in Full state feedback, Matrix and Applied mathematics. His Linear system research is multidisciplinary, incorporating elements of Lead–lag compensator, MIMO, Invariant, Link and Constant. His work deals with themes such as Discrete mathematics, Directed graph and Spanning tree, which intersect with Lyapunov function.
His primary areas of study are Control theory, Control theory, Transmission Control Protocol, Control system and Network packet. His Control theory study frequently involves adjacent topics like Series. His study in Control theory is interdisciplinary in nature, drawing from both Exponential stability, State and Hidden Markov model.
The Exponential stability study combines topics in areas such as Optimization problem, Applied mathematics and Exponential function. Zhan Shu interconnects Minimum mean square error, Convergence and Packet loss in the investigation of issues within Transmission Control Protocol. His research integrates issues of Stability and Optimal estimation in his study of Control system.
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Passivity-Based Asynchronous Control for Markov Jump Systems
Zheng-Guang Wu;Peng Shi;Zhan Shu;Hongye Su.
IEEE Transactions on Automatic Control (2017)
Positive Observers and Dynamic Output-Feedback Controllers for Interval Positive Linear Systems
Zhan Shu;J. Lam;Huijun Gao;Baozhu Du.
IEEE Transactions on Circuits and Systems I-regular Papers (2008)
Robust H∞ control of descriptor discrete-time markovian jump systems
James Lam;Zhan Shu;Shengyuan Xu;El-Kébir Boukas.
International Journal of Control (2007)
ℓ1-induced norm and controller synthesis of positive systems
Xiaoming Chen;James Lam;Ping Li;Zhan Shu.
Automatica (2013)
Passive vehicle suspensions employing inerters with multiple performance requirements
Yinlong Hu;Michael Zhi Qiang Chen;Zhan Shu.
Journal of Sound and Vibration (2014)
Analysis and optimisation for inerter-based isolators via fixed-point theory and algebraic solution
Yinlong Hu;Michael Z.Q. Chen;Zhan Shu;Lixi Huang.
Journal of Sound and Vibration (2015)
Consensus of Multiagent Systems Using Aperiodic Sampled-Data Control
Yuanqing Wu;Hongye Su;Peng Shi;Zhan Shu.
IEEE Transactions on Systems, Man, and Cybernetics (2016)
Optimal Estimation in UDP-Like Networked Control Systems With Intermittent Inputs: Stability Analysis and Suboptimal Filter Design
Hong Lin;Hongye Su;Zhan Shu;Zheng-Guang Wu.
IEEE Transactions on Automatic Control (2016)
Brief paper: Static output-feedback stabilization of discrete-time Markovian jump linear systems: A system augmentation approach
Zhan Shu;James Lam;Junlin Xiong.
Automatica (2010)
H∞ control of Markov jump time-delay systems under asynchronous controller and quantizer
Ying Shen;Zheng-Guang Wu;Peng Shi;Zhan Shu.
Automatica (2019)
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