What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Machine learning
His primary areas of investigation include Control theory, Nonlinear system, Fuzzy logic, Adaptive control and Backstepping.
He interconnects Bounded function and Multilayer perceptron in the investigation of issues within Control theory.
His studies in Nonlinear system integrate themes in fields like Control system, Multi-agent system, Artificial neural network and Adaptive system.
His study in the fields of Fuzzy control system under the domain of Fuzzy logic overlaps with other disciplines such as Stochastic process.
His Fuzzy control system study incorporates themes from Nonlinear control and Fuzzy set.
His Backstepping study is concerned with the field of Control engineering as a whole.
His most cited work include:
- Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems (264 citations)
- Fuzzy Adaptive Quantized Control for a Class of Stochastic Nonlinear Uncertain Systems (157 citations)
- Neural‐network‐based adaptive leader‐following consensus control for second‐order non‐linear multi‐agent systems (151 citations)
What are the main themes of his work throughout his whole career to date?
Zhi Liu mainly investigates Control theory, Nonlinear system, Fuzzy logic, Backstepping and Actuator.
Control theory and Bounded function are commonly linked in his work.
His Nonlinear system research focuses on Artificial neural network and how it relates to Multi-agent system.
In general Fuzzy logic, his work in Neuro-fuzzy, Defuzzification and Fuzzy set is often linked to Stochastic process linking many areas of study.
His Backstepping study combines topics in areas such as Tracking and Exponential stability.
His research integrates issues of Stability, Mechanical system, Compensation and Backlash in his study of Actuator.
He most often published in these fields:
- Control theory (80.00%)
- Nonlinear system (56.13%)
- Fuzzy logic (38.06%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (80.00%)
- Nonlinear system (56.13%)
- Backstepping (27.74%)
In recent papers he was focusing on the following fields of study:
Zhi Liu mostly deals with Control theory, Nonlinear system, Backstepping, Control theory and Fuzzy logic.
His work in Control theory covers topics such as Multi-agent system which are related to areas like Computer simulation.
His Nonlinear system research incorporates themes from Artificial neural network, Stability, Bounded function, Adaptive system and Dead zone.
His Control theory research focuses on Quantization and how it connects with Trajectory.
His studies in Fuzzy logic integrate themes in fields like Control system, Control and Wavelet, Pattern recognition.
His biological study spans a wide range of topics, including Backlash, Tracking and Adaptive control.
Between 2019 and 2021, his most popular works were:
- Adaptive Neural Control of a Class of Stochastic Nonlinear Uncertain Systems With Guaranteed Transient Performance (22 citations)
- Fuzzy Adaptive Two-Bit-Triggered Control for a Class of Uncertain Nonlinear Systems With Actuator Failures and Dead-Zone Constraint (21 citations)
- Leader-Following Consensus for a Class of Nonlinear Strick-Feedback Multiagent Systems With State Time-Delays (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
His scientific interests lie mostly in Control theory, Nonlinear system, Backstepping, Actuator and Tracking error.
His research links Artificial neural network with Control theory.
His Artificial neural network study combines topics from a wide range of disciplines, such as Control system and Instability.
Zhi Liu regularly links together related areas like Fuzzy control system in his Nonlinear system studies.
As part of one scientific family, he deals mainly with the area of Backstepping, narrowing it down to issues related to the Multi-agent system, and often Tracking and Synchronization.
His Control theory research includes elements of Lyapunov function and Fuzzy logic.
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