2015 - IEEE Fellow For contributions to stability analysis of recurrent neural networks and intelligent control of nonlinear systems
His main research concerns Control theory, Artificial neural network, Nonlinear system, Mathematical optimization and Optimal control. His Control theory study focuses mostly on Control theory, Stability, Linear matrix inequality, Fuzzy control system and Adaptive control. He has included themes like Reinforcement learning, Exponential stability, Lyapunov function and Stability conditions in his Artificial neural network study.
His studies in Nonlinear system integrate themes in fields like Control system and Approximation theory. He interconnects Discrete time and continuous time, Bounded function and Linear system in the investigation of issues within Mathematical optimization. His Optimal control research is multidisciplinary, relying on both Convergence, Dynamic programming and Parametric statistics.
Huaguang Zhang spends much of his time researching Control theory, Nonlinear system, Artificial neural network, Mathematical optimization and Control theory. His Control theory study frequently involves adjacent topics like Fuzzy logic. Huaguang Zhang works mostly in the field of Nonlinear system, limiting it down to topics relating to Actuator and, in certain cases, Fault tolerance.
His work investigates the relationship between Artificial neural network and topics such as Exponential stability that intersect with problems in Equilibrium point. His Mathematical optimization study combines topics in areas such as Function, Convergence and Multi-agent system. His Optimal control research incorporates themes from Iterative method and Dynamic programming.
The scientist’s investigation covers issues in Control theory, Nonlinear system, Multi-agent system, Control theory and Fuzzy logic. His studies link Control with Control theory. Huaguang Zhang has researched Nonlinear system in several fields, including Artificial neural network and Optimal control.
His study in Optimal control is interdisciplinary in nature, drawing from both Stability, Echo state network, Dynamic programming and Reinforcement learning. His Control theory research integrates issues from Network topology, Topology and Noise. His research integrates issues of Finite time and Piecewise in his study of Fuzzy logic.
His scientific interests lie mostly in Multi-agent system, Control theory, Nonlinear system, Consensus and Control theory. The Multi-agent system study combines topics in areas such as Control, Event triggered, Distributed computing, Bipartite graph and Topology. His study ties his expertise on Reinforcement learning together with the subject of Control theory.
His work deals with themes such as Optimal control, Artificial neural network, Stability, Dynamic programming and Fuzzy logic, which intersect with Nonlinear system. His Artificial neural network research focuses on Robustness and how it relates to Vehicle dynamics. His work carried out in the field of Consensus brings together such families of science as Theoretical computer science and Output feedback.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Adaptive Dynamic Programming: An Introduction
Fei-Yue Wang;Huaguang Zhang;Derong Liu.
IEEE Computational Intelligence Magazine (2009)
Neural-Network-Based Near-Optimal Control for a Class of Discrete-Time Affine Nonlinear Systems With Control Constraints
Huaguang Zhang;Yanhong Luo;Derong Liu.
IEEE Transactions on Neural Networks (2009)
Data-Driven Robust Approximate Optimal Tracking Control for Unknown General Nonlinear Systems Using Adaptive Dynamic Programming Method
Huaguang Zhang;Lili Cui;Xin Zhang;Yanhong Luo.
IEEE Transactions on Neural Networks (2011)
A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2014)
A Novel Infinite-Time Optimal Tracking Control Scheme for a Class of Discrete-Time Nonlinear Systems via the Greedy HDP Iteration Algorithm
Huaguang Zhang;Qinglai Wei;Yanhong Luo.
systems man and cybernetics (2008)
A Combined Backstepping and Small-Gain Approach to Robust Adaptive Fuzzy Output Feedback Control
Shao-Cheng Tong;Xiang-Lei He;Hua-Guang Zhang.
IEEE Transactions on Fuzzy Systems (2009)
Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay
Huaguang Zhang;Zhenwei Liu;Guang-Bin Huang;Zhanshan Wang.
IEEE Transactions on Neural Networks (2010)
Robust Global Exponential Synchronization of Uncertain Chaotic Delayed Neural Networks via Dual-Stage Impulsive Control
Huaguang Zhang;Tiedong Ma;Guang-Bin Huang;Zhiliang Wang.
systems man and cybernetics (2010)
An iterative adaptive dynamic programming method for solving a class of nonlinear zero-sum differential games
Huaguang Zhang;Qinglai Wei;Derong Liu.
Global Asymptotic Stability of Recurrent Neural Networks With Multiple Time-Varying Delays
Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2008)
Profile was last updated on December 6th, 2021.
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