The scientist’s investigation covers issues in Control theory, Synchronization, Mathematical optimization, Multi-agent system and Lyapunov function. His research in Control theory is mostly focused on Nonlinear system. His research in Synchronization tackles topics such as Artificial neural network which are related to areas like Mode, Exponential synchronization and Intermittent control.
His Mathematical optimization study deals with Network topology intersecting with Exponential stability, Moment and Stability. The Multi-agent system study combines topics in areas such as Stochastic process and Control. His Lyapunov function research focuses on Adaptive control and how it connects with Bernoulli's principle.
Yang Tang mainly investigates Control theory, Mathematical optimization, Multi-agent system, Synchronization and Stability. His work carried out in the field of Control theory brings together such families of science as Artificial neural network and Stochastic process. Yang Tang works mostly in the field of Multi-agent system, limiting it down to topics relating to Control and, in certain cases, Tracking, as a part of the same area of interest.
His Synchronization research incorporates themes from Coupling, Adaptive control, Computer simulation and Amplitude death. Many of his research projects under Stability are closely connected to Synchronization with Synchronization, tying the diverse disciplines of science together. His Evolutionary algorithm study which covers Evolutionary computation that intersects with Controllability and Topology.
Yang Tang spends much of his time researching Control theory, Multi-agent system, Artificial intelligence, Topology and Control. His Control theory research includes elements of Markov process, Position and Synchronization. The various areas that Yang Tang examines in his Multi-agent system study include Distributed computing, Convergence, Lyapunov function, Tracking error and Piecewise.
His study in Lyapunov function is interdisciplinary in nature, drawing from both Network topology, Consensus, Markov chain and Stability. Topology and Controllability are frequently intertwined in his study. His work deals with themes such as Artificial neural network and Bounded function, which intersect with Control theory.
Yang Tang focuses on Multi-agent system, Control theory, Nonlinear system, Convergence and Artificial intelligence. His studies deal with areas such as Control, Tracking error, Protocol and Directed graph as well as Multi-agent system. Within one scientific family, Yang Tang focuses on topics pertaining to Synchronization under Control theory, and may sometimes address concerns connected to Control theory.
The study incorporates disciplines such as Chain, CHAOS, Markov process, Complex system and Focus in addition to Nonlinear system. His study looks at the relationship between Convergence and topics such as Settling time, which overlap with Terminal sliding mode and Exponential stability. Yang Tang has researched Artificial intelligence in several fields, including Automatic control and Human–computer interaction.
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Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings
Yang Tang;Huijun Gao;Wei Zou;Jürgen Kurths.
IEEE Transactions on Systems, Man, and Cybernetics (2013)
Leader-following consensus of a class of stochastic delayed multi-agent systems with partial mixed impulses
Yang Tang;Huijun Gao;Wenbing Zhang;Jürgen Kurths.
Synchronization in complex networks and its application – A survey of recent advances and challenges
Yang Tang;Yang Tang;Feng Qian;Huijun Gao;Huijun Gao;Jürgen Kurths.
Annual Reviews in Control (2014)
Tracking Control of Networked Multi-Agent Systems Under New Characterizations of Impulses and Its Applications in Robotic Systems
Yang Tang;Xing Xing;Hamid Reza Karimi;Ljupco Kocarev.
IEEE Transactions on Industrial Electronics (2016)
Event-Triggered Control for Consensus Problem in Multi-Agent Systems With Quantized Relative State Measurements and External Disturbance
Zheng-Guang Wu;Yong Xu;Ya-Jun Pan;Housheng Su.
IEEE Transactions on Circuits and Systems I-regular Papers (2018)
Distributed Synchronization of Coupled Neural Networks via Randomly Occurring Control
Yang Tang;Wai Keung Wong.
IEEE Transactions on Neural Networks (2013)
Exponential Synchronization of Coupled Switched Neural Networks With Mode-Dependent Impulsive Effects
Wenbing Zhang;Yang Tang;Qingying Miao;Wei Du.
IEEE Transactions on Neural Networks (2013)
Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses
Wenbing Zhang;Yang Tang;Tingwen Huang;Jurgen Kurths.
IEEE Transactions on Neural Networks (2017)
On Controllability of Delayed Boolean Control Networks
Jianquan Lu;Jie Zhong;Daniel W. C. Ho;Yang Tang.
Siam Journal on Control and Optimization (2016)
Input-to-state stability of impulsive stochastic delayed systems under linear assumptions
Xiaotai Wu;Yang Tang;Wenbing Zhang.
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