What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Mechanical engineering
His primary areas of investigation include Control theory, Iterative learning control, Linear system, Iterative method and Mathematical optimization.
His research on Control theory frequently connects to adjacent areas such as Control engineering.
His Iterative learning control research is multidisciplinary, incorporating perspectives in Rehabilitation, Optimal control, Convergence, Feed forward and Robustness.
Eric Rogers has included themes like Stability, Control theory, Controllability and Multidimensional systems in his Linear system study.
Within one scientific family, he focuses on topics pertaining to Rate of convergence under Iterative method, and may sometimes address concerns connected to Discrete system, Learning controller, Control synthesis, H-infinity methods in control theory and Design methods.
Eric Rogers focuses mostly in the field of Mathematical optimization, narrowing it down to topics relating to Controller design and, in certain cases, Ranging and Stability conditions.
His most cited work include:
- Iterative learning control for discrete-time systems with exponential rate of convergence (313 citations)
- Stability Analysis for Linear Repetitive Processes (260 citations)
- Iterative learning control using optimal feedback and feedforward actions (256 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Control theory, Iterative learning control, Linear system, Control engineering and Mathematical optimization.
His work in Control theory, Stability, Exponential stability, Nonlinear system and Stability theory are all subfields of Control theory research.
His work deals with themes such as Linear matrix inequality and Process control, which intersect with Exponential stability.
He usually deals with Iterative learning control and limits it to topics linked to Rehabilitation and Task.
While the research belongs to areas of Linear system, Eric Rogers spends his time largely on the problem of Systems theory, intersecting his research to questions surrounding Class.
He studies Optimal control, a branch of Mathematical optimization.
He most often published in these fields:
- Control theory (58.26%)
- Iterative learning control (35.74%)
- Linear system (22.28%)
What were the highlights of his more recent work (between 2013-2021)?
- Control theory (58.26%)
- Iterative learning control (35.74%)
- Nonlinear system (7.47%)
In recent papers he was focusing on the following fields of study:
His main research concerns Control theory, Iterative learning control, Nonlinear system, Exponential stability and Stability theory.
As part of his studies on Control theory, Eric Rogers often connects relevant subjects like Control engineering.
His biological study spans a wide range of topics, including Process control, Process, Convergence, Task and Mathematical optimization.
His Nonlinear system study deals with Differential intersecting with Class.
His Exponential stability research integrates issues from Control system and Applied mathematics.
His Stability theory research is multidisciplinary, relying on both Control theory and Bounded function.
Between 2013 and 2021, his most popular works were:
- Experimentally verified generalized KYP Lemma based iterative learning control design (61 citations)
- The application of precisely controlled functional electrical stimulation to the shoulder, elbow and wrist for upper limb stroke rehabilitation: a feasibility study (53 citations)
- Multidimensional control systems: case studies in design and evaluation (53 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Artificial intelligence
- Mathematical analysis
His primary scientific interests are in Control theory, Iterative learning control, Nonlinear system, Stability and Stability theory.
His Control theory study combines topics in areas such as Differential, Convergence and Process.
The Iterative learning control study combines topics in areas such as Task, Control engineering, Iterative method, Mathematical optimization and Trajectory.
His Mathematical optimization research is multidisciplinary, incorporating elements of Systems theory, Linear system, Monotonic function and Stability conditions.
He interconnects Class, Linear model and Robust control in the investigation of issues within Stability.
His research investigates the link between Stability theory and topics such as Control theory that cross with problems in Time domain, Feed forward, Simulation, Actuator and Attitude control.
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