What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Machine learning
His primary areas of investigation include Control theory, Iterative learning control, Nonlinear system, Mathematical optimization and Control engineering.
His studies in Control theory, Robust control, Lyapunov function, Torque and Nonlinear control are all subfields of Control theory research.
Jian-Xin Xu interconnects Control system, Iterative method, Tracking error, Adaptive control and Robustness in the investigation of issues within Iterative learning control.
His Adaptive control research incorporates elements of Time domain and Electronic speed control.
His study explores the link between Nonlinear system and topics such as Function that cross with problems in MIMO.
His work deals with themes such as Intelligent control, Optimal design, Economic dispatch and Lipschitz continuity, which intersect with Mathematical optimization.
His most cited work include:
- Iterative Learning Control (471 citations)
- Consensus Based Approach for Economic Dispatch Problem in a Smart Grid (439 citations)
- Iterative learning control: analysis, design, integration and applications (355 citations)
What are the main themes of his work throughout his whole career to date?
Control theory, Iterative learning control, Nonlinear system, Control engineering and Control theory are his primary areas of study.
His Control theory study frequently links to adjacent areas such as Mathematical optimization.
His Iterative learning control study incorporates themes from Linear system, Tracking, Trajectory, Iterative method and Lipschitz continuity.
His Nonlinear system research is multidisciplinary, incorporating elements of Discrete time and continuous time, Internal model, Multi-agent system, Function and Robustness.
As a part of the same scientific study, Jian-Xin Xu usually deals with the Control engineering, concentrating on Torque and frequently concerns with Direct torque control.
His work in Control theory covers topics such as PWM rectifier which are related to areas like Harmonics.
He most often published in these fields:
- Control theory (74.85%)
- Iterative learning control (38.24%)
- Nonlinear system (26.58%)
What were the highlights of his more recent work (between 2014-2020)?
- Control theory (74.85%)
- Iterative learning control (38.24%)
- Nonlinear system (26.58%)
In recent papers he was focusing on the following fields of study:
Jian-Xin Xu spends much of his time researching Control theory, Iterative learning control, Nonlinear system, Control theory and Mathematical optimization.
His Control theory research includes elements of Control engineering and Robot, Motion control.
His Iterative learning control research is multidisciplinary, incorporating perspectives in Tracking, Tracking error, Multi-agent system, Algorithm and Lipschitz continuity.
His research investigates the connection with Nonlinear system and areas like Control system which intersect with concerns in MIMO.
His research in Control theory intersects with topics in Steady state and Feed forward.
His Mathematical optimization study combines topics in areas such as Algorithm design and Robustness.
Between 2014 and 2020, his most popular works were:
- Precise Speed Tracking Control of a Robotic Fish Via Iterative Learning Control (66 citations)
- Adaptive Cross-Generation Differential Evolution Operators for Multiobjective Optimization (64 citations)
- Iterative learning control design for linear discrete-time systems with multiple high-order internal models (57 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
His primary areas of study are Iterative learning control, Control theory, Nonlinear system, Mathematical optimization and Multi-agent system.
His Iterative learning control research includes themes of Norm, Tracking error, Trajectory and Applied mathematics.
His work in the fields of Control theory overlaps with other areas such as Nonparametric statistics.
His Nonlinear system study combines topics from a wide range of disciplines, such as Control system and Lipschitz continuity.
He has researched Mathematical optimization in several fields, including Markov renewal process, Markov chain and Robustness.
His biological study spans a wide range of topics, including Group, Distributed computing, State and Robot manipulator.
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