What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Statistics
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.
His most cited work include:
- Adaptive Dynamic Programming: An Introduction (614 citations)
- Neural-Network-Based Near-Optimal Control for a Class of Discrete-Time Affine Nonlinear Systems With Control Constraints (462 citations)
- A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks (378 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Control theory (64.65%)
- Nonlinear system (30.14%)
- Artificial neural network (29.44%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (64.65%)
- Nonlinear system (30.14%)
- Multi-agent system (10.42%)
In recent papers he was focusing on the following fields of study:
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.
Between 2019 and 2021, his most popular works were:
- Neural-Network-Based Event-Triggered Adaptive Control of Nonaffine Nonlinear Multiagent Systems With Dynamic Uncertainties (43 citations)
- A hybrid wind power forecasting approach based on Bayesian model averaging and ensemble learning (23 citations)
- Adaptive Bipartite Event-Triggered Output Consensus of Heterogeneous Linear Multiagent Systems Under Fixed and Switching Topologies (19 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Artificial intelligence
- Statistics
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.
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