What is he best known for?
The fields of study he is best known for:
- Control theory
- Mechanical engineering
- Artificial intelligence
His primary areas of study are Robust control, Control theory, Adaptive control, Control engineering and Motion control.
His Robust control research is within the category of Control theory.
Bin Yao is involved in the study of Control theory that focuses on Nonlinear system in particular.
The various areas that he examines in his Adaptive control study include Sliding mode control and Exponential stability.
His study in Control engineering is interdisciplinary in nature, drawing from both Control system, Parallel manipulator, Compensation and Lyapunov function.
In his study, System identification is strongly linked to Tracking error, which falls under the umbrella field of Motion control.
His most cited work include:
- Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form (528 citations)
- Adaptive robust motion control of single-rod hydraulic actuators: theory and experiments (468 citations)
- Polypyrrole-coated paper for flexible solid-state energy storage (430 citations)
What are the main themes of his work throughout his whole career to date?
Bin Yao spends much of his time researching Control theory, Robust control, Control engineering, Adaptive control and Control theory.
Many of his studies on Control theory involve topics that are commonly interrelated, such as Motion control.
His Robust control study incorporates themes from Estimation theory, Tracking error, Compensation and Backstepping.
His work on Variable structure control as part of general Control engineering study is frequently linked to Transient, therefore connecting diverse disciplines of science.
His biological study spans a wide range of topics, including Sliding mode control, Exponential stability, Nonlinear control and Observer.
His Control theory research integrates issues from Tracking, Simulation and Trajectory.
He most often published in these fields:
- Control theory (84.79%)
- Robust control (60.57%)
- Control engineering (48.97%)
What were the highlights of his more recent work (between 2015-2021)?
- Control theory (84.79%)
- Robust control (60.57%)
- Motion control (29.64%)
In recent papers he was focusing on the following fields of study:
Control theory, Robust control, Motion control, Control theory and Nonlinear system are his primary areas of study.
His work carried out in the field of Control theory brings together such families of science as Control engineering and Hydraulic machinery.
He has researched Robust control in several fields, including Motion controller, Artificial neural network and Adaptive control.
His Motion control study combines topics from a wide range of disciplines, such as Compensation, Hydraulic cylinder and Match moving.
His Control theory research is multidisciplinary, incorporating perspectives in Control system, Estimation theory, Tracking, Feed forward and Robot.
His studies in Nonlinear system integrate themes in fields like Frequency response, Flow and Robustness.
Between 2015 and 2021, his most popular works were:
- Paper-Based Electrodes for Flexible Energy Storage Devices. (174 citations)
- Flexible Transparent Molybdenum Trioxide Nanopaper for Energy Storage (137 citations)
- Flexible Transparent Molybdenum Trioxide Nanopaper for Energy Storage (137 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Mechanical engineering
- Artificial intelligence
His primary areas of study are Supercapacitor, Nanotechnology, Control theory, Capacitance and Energy storage.
The Supercapacitor study combines topics in areas such as Oxide and Chemical engineering.
His Control theory study is mostly concerned with Trajectory, Nonlinear system, Control theory, Torque and Robust control.
The study incorporates disciplines such as Control engineering, Cascade and Hydraulic machinery in addition to Nonlinear system.
His Robust control study deals with the bigger picture of Robustness.
His Capacitance research includes elements of Optoelectronics and Graphene.
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.
