What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Operating system
His primary areas of investigation include Control theory, Control engineering, Linear system, Control system and Nonlinear system.
In his study, Multivariable calculus is strongly linked to Matrix, which falls under the umbrella field of Control theory.
In his work, Transceiver, Inertial measurement unit, Motion planning and Feature is strongly intertwined with Remotely operated underwater vehicle, which is a subfield of Control engineering.
His work carried out in the field of Linear system brings together such families of science as Bilinear interpolation and Applied mathematics.
His study in Control system is interdisciplinary in nature, drawing from both Software system, Real-time computing and Systems engineering.
His Control theory research is multidisciplinary, relying on both Lemma and Subject.
His most cited work include:
- Brief An analysis and design method for linear systems subject to actuator saturation and disturbance (652 citations)
- Composite nonlinear feedback control for linear systems with input saturation: theory and an application (370 citations)
- Analysis and design for discrete-time linear systems subject to actuator saturation☆ (350 citations)
What are the main themes of his work throughout his whole career to date?
Ben M. Chen mainly focuses on Control theory, Control engineering, Linear system, Control theory and Nonlinear system.
Servomechanism, Control system, Optimal control, Robust control and Actuator are the core of his Control theory study.
His biological study spans a wide range of topics, including Servo, Servo drive, Settling time and Track.
His studies deal with areas such as Transfer function, Invertible matrix and Infimum and supremum as well as Optimal control.
His Control engineering research is multidisciplinary, incorporating elements of Control, Remotely operated underwater vehicle and Trajectory.
The Linear system study combines topics in areas such as Zero, Matrix and Invariant.
He most often published in these fields:
- Control theory (50.00%)
- Control engineering (21.73%)
- Linear system (14.14%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (14.35%)
- Computer vision (10.76%)
- Control theory (50.00%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Control theory, Trajectory and Control engineering.
He works mostly in the field of Artificial intelligence, limiting it down to topics relating to Global Positioning System and, in certain cases, Real-time computing and Navigation system.
His Computer vision research includes elements of Simultaneous localization and mapping and Visual odometry.
His work on Nonlinear system as part of general Control theory research is frequently linked to Angular acceleration, thereby connecting diverse disciplines of science.
His Trajectory research incorporates elements of Series and Vehicle dynamics.
The various areas that Ben M. Chen examines in his Control engineering study include Intelligent control, Complex system and Robustness.
Between 2015 and 2021, his most popular works were:
- SO-Net: Self-Organizing Network for Point Cloud Analysis (271 citations)
- SO-Net: Self-Organizing Network for Point Cloud Analysis (70 citations)
- A robust online path planning approach in cluttered environments for micro rotorcraft drones (37 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Operating system
Ben M. Chen focuses on Artificial intelligence, Computer vision, Trajectory, Real-time computing and Control theory.
His Computer vision research includes themes of Mobile robot navigation, Simultaneous localization and mapping and Dead reckoning, Global Positioning System.
The study incorporates disciplines such as Control engineering, Construct and Smoothing in addition to Trajectory.
His work on Autopilot as part of general Control engineering research is frequently linked to Core component, bridging the gap between disciplines.
His Real-time computing study combines topics from a wide range of disciplines, such as Extended Kalman filter, Ultra-wideband, Swarm behaviour, Simulation and 3d localization.
His Control theory study integrates concerns from other disciplines, such as Solver, Task and Bounding overwatch.
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