What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Mathematical analysis
Guang-Hong Yang mainly investigates Control theory, Control theory, Nonlinear system, Actuator and Linear system.
The concepts of his Control theory study are interwoven with issues in Control engineering and Fuzzy logic.
His Control theory research is multidisciplinary, relying on both State, Multi-agent system, Linearization and Directed graph.
The Nonlinear system study combines topics in areas such as Stability, Artificial neural network and Adaptive system.
As a part of the same scientific family, he mostly works in the field of Actuator, focusing on Fault tolerance and, on occasion, Control reconfiguration, Semidefinite programming, Sum-of-squares optimization and Optimization problem.
He has researched Linear system in several fields, including Time complexity, Discrete time and continuous time, Exponential stability, Fault detection and isolation and Linear-quadratic-Gaussian control.
His most cited work include:
- Reliable robust flight tracking control: an LMI approach (476 citations)
- Brief Reliable H∞ controller design for linear systems (420 citations)
- Adaptive Fault-Tolerant Tracking Control Against Actuator Faults With Application to Flight Control (412 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Control theory, Nonlinear system, Control theory, Linear system and Actuator.
His Control theory study frequently links to other fields, such as Control engineering.
His Control engineering research is multidisciplinary, incorporating elements of Control reconfiguration and State.
In his study, Affine transformation is inextricably linked to Fuzzy logic, which falls within the broad field of Nonlinear system.
His Control theory study incorporates themes from Observer, Control, Multi-agent system and Stability theory.
His Linear system research includes elements of Discrete time and continuous time, Exponential stability, Robust control, Fault detection and isolation and Mathematical optimization.
He most often published in these fields:
- Control theory (97.41%)
- Nonlinear system (27.03%)
- Control theory (27.36%)
What were the highlights of his more recent work (between 2017-2021)?
- Control theory (97.41%)
- Nonlinear system (27.03%)
- Control theory (27.36%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Control theory, Nonlinear system, Control theory, Fuzzy logic and Observer.
Control theory connects with themes related to Fault tolerance in his study.
His Nonlinear system study combines topics in areas such as Artificial neural network and Stability.
His work deals with themes such as Control system, Stability theory, Control, Multi-agent system and Bounded function, which intersect with Control theory.
His study in Observer is interdisciplinary in nature, drawing from both Linear system and Cyber-physical system.
As a part of the same scientific study, he usually deals with the Fuzzy control system, concentrating on Fault detection and isolation and frequently concerns with Residual.
Between 2017 and 2021, his most popular works were:
- Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems (111 citations)
- Event-Triggered Fault Detection Filter Design for Nonlinear Networked Systems (110 citations)
- Neural-Network-Based Adaptive Decentralized Fault-Tolerant Control for a Class of Interconnected Nonlinear Systems (107 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Artificial intelligence
- Mathematical analysis
Guang-Hong Yang mainly focuses on Control theory, Nonlinear system, Control theory, Adaptive system and Actuator.
The study incorporates disciplines such as Fault tolerance and Fuzzy logic in addition to Control theory.
His Nonlinear system research includes themes of Artificial neural network, Discrete time and continuous time and Stability.
His Control theory research integrates issues from Control system, Event triggered, Exponential stability, Multi-agent system and Bounded function.
He focuses mostly in the field of Adaptive system, narrowing it down to topics relating to State observer and, in certain cases, Output feedback, Tracking, Synchronization and State vector.
His work in Actuator covers topics such as Trajectory which are related to areas like Controllability, Boundary, High gain observer and Feedback linearization.
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.
