What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Machine learning
Shuzhi Sam Ge focuses on Control theory, Adaptive control, Lyapunov function, Nonlinear system and Backstepping.
His Control theory study combines topics in areas such as Artificial neural network and Control engineering.
His Control engineering research incorporates elements of Stability, Robot and Trajectory.
His Adaptive control research is multidisciplinary, relying on both Control system, Robust control, Variable structure control, Bounded function and Adaptive system.
His Lyapunov function research focuses on subjects like Boundary, which are linked to Distributed parameter system and Partial differential equation.
His studies in Nonlinear system integrate themes in fields like Discrete time and continuous time, Control, MIMO, Mathematical optimization and Bounding overwatch.
His most cited work include:
- Barrier Lyapunov Functions for the control of output-constrained nonlinear systems (1060 citations)
- Switched Linear Systems: Control and Design (831 citations)
- New potential functions for mobile robot path planning (647 citations)
What are the main themes of his work throughout his whole career to date?
Shuzhi Sam Ge mostly deals with Control theory, Adaptive control, Nonlinear system, Artificial neural network and Control engineering.
Shuzhi Sam Ge has researched Control theory in several fields, including Robot and Bounded function.
His Adaptive control research incorporates elements of Control system, Robust control, Nonlinear control, Tracking error and Adaptive system.
His studies deal with areas such as MIMO, Discrete time and continuous time and Mathematical optimization as well as Nonlinear system.
His study in Artificial neural network is interdisciplinary in nature, drawing from both Tracking and Trajectory.
He combines subjects such as Stability, Control, Actuator and System dynamics with his study of Control engineering.
He most often published in these fields:
- Control theory (68.22%)
- Adaptive control (35.14%)
- Nonlinear system (25.49%)
What were the highlights of his more recent work (between 2017-2021)?
- Control theory (68.22%)
- Artificial intelligence (18.98%)
- Control theory (19.41%)
In recent papers he was focusing on the following fields of study:
Shuzhi Sam Ge mainly focuses on Control theory, Artificial intelligence, Control theory, Control and Nonlinear system.
Shuzhi Sam Ge works mostly in the field of Control theory, limiting it down to topics relating to Artificial neural network and, in certain cases, Lyapunov stability, as a part of the same area of interest.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Computer vision and Pattern recognition.
His study in Control focuses on Adaptive control in particular.
His work is dedicated to discovering how Nonlinear system, Reinforcement learning are connected with Optimal control and other disciplines.
Shuzhi Sam Ge has included themes like Exponential stability and Linear system in his Lyapunov function study.
Between 2017 and 2021, his most popular works were:
- Unified iterative learning control for flexible structures with input constraints (153 citations)
- An Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control for Robust Fault Tolerant Control of Robot Manipulators (87 citations)
- Optimized Backstepping for Tracking Control of Strict-Feedback Systems (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Machine learning
Shuzhi Sam Ge mainly focuses on Control theory, Nonlinear system, Artificial neural network, Control and Trajectory.
His Control theory study integrates concerns from other disciplines, such as Robot and Tracking.
His Nonlinear system study incorporates themes from Mathematical optimization, Applied mathematics, Mixture model, Collision and Conditional probability distribution.
The Artificial neural network study combines topics in areas such as Salient, System model, Lyapunov stability, Focus and Reinforcement learning.
His research investigates the link between Control and topics such as Control system that cross with problems in Visualization, Protocol and Strict-feedback form.
His research integrates issues of Exponential stability and Aerodynamics in his study of Lyapunov function.
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