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 study are Control theory, Control theory, Nonlinear system, Adaptive control and Exponential stability.
His Control theory research incorporates elements of Artificial neural network, Control engineering and Fuzzy logic.
His work deals with themes such as Bounded function, Vehicle dynamics and Feed forward, which intersect with Artificial neural network.
His studies deal with areas such as Robot and Actuator as well as Control engineering.
His research investigates the link between Control theory and topics such as Stability that cross with problems in Adaptive algorithm and Computation.
His Adaptive control study often links to related topics such as Tracking error.
His most cited work include:
- Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle (219 citations)
- Neural network-based sliding mode adaptive control for robot manipulators (170 citations)
- Adaptive Fuzzy Backstepping Control of Fractional-Order Nonlinear Systems (165 citations)
What are the main themes of his work throughout his whole career to date?
Yongping Pan mainly investigates Control theory, Adaptive control, Nonlinear system, Exponential stability and Artificial neural network.
His work on Control theory, Lyapunov function, Tracking error and Backstepping as part of general Control theory study is frequently connected to Parametric statistics, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Adaptive control research focuses on subjects like Fuzzy control system, which are linked to Local convergence and Function approximation.
His Nonlinear system research focuses on Stability and how it connects with Control system.
His Exponential stability study combines topics from a wide range of disciplines, such as Separation principle, Least squares and Applied mathematics.
Yongping Pan combines subjects such as Control and Trajectory with his study of Artificial neural network.
He most often published in these fields:
- Control theory (79.34%)
- Adaptive control (35.54%)
- Nonlinear system (34.71%)
What were the highlights of his more recent work (between 2018-2021)?
- Control theory (79.34%)
- Nonlinear system (34.71%)
- Adaptive control (35.54%)
In recent papers he was focusing on the following fields of study:
Yongping Pan mostly deals with Control theory, Nonlinear system, Adaptive control, Robustness and Control theory.
His Control theory study incorporates themes from Robot and Estimation theory.
Yongping Pan mostly deals with Backstepping in his studies of Nonlinear system.
Yongping Pan works mostly in the field of Backstepping, limiting it down to topics relating to Tracking error and, in certain cases, Adaptive system.
His study in Adaptive control is interdisciplinary in nature, drawing from both Artificial neural network and Identification.
His Robustness research incorporates themes from Stability and Trajectory.
Between 2018 and 2021, his most popular works were:
- Efficient PID Tracking Control of Robotic Manipulators Driven by Compliant Actuators (43 citations)
- Composite Learning Adaptive Dynamic Surface Control of Fractional-Order Nonlinear Systems (33 citations)
- Composite Learning Robot Control With Friction Compensation: A Neural Network-Based Approach (30 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
Control theory, Nonlinear system, Robot, Exponential stability and Actuator are his primary areas of study.
The study of Control theory is intertwined with the study of Artificial neural network in a number of ways.
His Artificial neural network research integrates issues from Composite number and Robot control.
His Nonlinear system course of study focuses on Fractional calculus and Bounded function and State variable.
His Robot research is multidisciplinary, incorporating perspectives in Singular perturbation and PID controller.
He has included themes like Adaptive control and Bounding overwatch in his Lyapunov function study.
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