What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Machine learning
His scientific interests lie mostly in Control theory, Control theory, Fuzzy logic, Fuzzy control system and Control system.
Jianqiang Yi has researched Control theory in several fields, including Control engineering and Artificial neural network.
His Control theory research is multidisciplinary, relying on both Simulation, Trajectory and Motion control.
His work on Fuzzy set as part of general Fuzzy logic research is often related to Pendulum, thus linking different fields of science.
His research integrates issues of Defuzzification and Inverted pendulum in his study of Fuzzy control system.
His Control system research includes themes of Overshoot, Exponential stability, Feedforward neural network and Variable sampling.
His most cited work include:
- Adaptive sliding mode fuzzy control for a two-dimensional overhead crane (201 citations)
- Building Energy Consumption Prediction: An Extreme Deep Learning Approach (120 citations)
- Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach (116 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Control theory, Control theory, Fuzzy logic, Control engineering and Fuzzy control system.
His studies in Control system, Nonlinear system, Adaptive control, Lyapunov function and Sliding mode control are all subfields of Control theory research.
His work carried out in the field of Control theory brings together such families of science as Artificial neural network and Trajectory.
Jianqiang Yi combines subjects such as Mathematical optimization and Interval with his study of Fuzzy logic.
His Control engineering research integrates issues from Mobile manipulator, Aerodynamics, Control, Vehicle dynamics and Robustness.
His work on Adaptive neuro fuzzy inference system is typically connected to Pendulum as part of general Fuzzy control system study, connecting several disciplines of science.
He most often published in these fields:
- Control theory (65.72%)
- Control theory (31.44%)
- Fuzzy logic (22.38%)
What were the highlights of his more recent work (between 2016-2021)?
- Control theory (65.72%)
- Adaptive control (14.73%)
- Lyapunov function (12.75%)
In recent papers he was focusing on the following fields of study:
Jianqiang Yi focuses on Control theory, Adaptive control, Lyapunov function, Fuzzy logic and Control theory.
His Control theory study frequently links to adjacent areas such as Hypersonic speed.
His studies in Adaptive control integrate themes in fields like Artificial neural network and Tracking.
His Lyapunov function study also includes
- Parametric statistics that connect with fields like Sliding mode control,
- Control engineering, Transient, State estimator and State most often made with reference to Aerodynamics.
His Fuzzy logic research is multidisciplinary, incorporating perspectives in Energy consumption, Mathematical optimization and Interval.
State observer is closely connected to Robust control in his research, which is encompassed under the umbrella topic of Fuzzy control system.
Between 2016 and 2021, his most popular works were:
- Building Energy Consumption Prediction: An Extreme Deep Learning Approach (120 citations)
- Analysis and Design of Functionally Weighted Single-Input-Rule-Modules Connected Fuzzy Inference Systems (57 citations)
- Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction (32 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
Jianqiang Yi mainly focuses on Control theory, Fuzzy logic, Lyapunov function, Vehicle dynamics and Backstepping.
His Control theory study focuses on Control theory in particular.
Jianqiang Yi interconnects Tracking and Hypersonic vehicle in the investigation of issues within Control theory.
His biological study spans a wide range of topics, including Algorithm design, Mathematical optimization and Multivariable calculus.
His Aerodynamics research focuses on subjects like Control system, which are linked to Disturbance observer and Robustness.
The concepts of his Parametric statistics study are interwoven with issues in Interval and Nonlinear system.
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