What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Electrical engineering
Control theory, Nonlinear system, Adaptive control, Control theory and Lyapunov function are his primary areas of study.
His work in Control theory is not limited to one particular discipline; it also encompasses Control engineering.
The various areas that Farshad Khorrami examines in his Control engineering study include Link, DC motor, Electric motor and Actuator.
His studies examine the connections between Nonlinear system and genetics, as well as such issues in Bounded function, with regards to State observer.
The study incorporates disciplines such as Estimation theory and Robustness in addition to Adaptive control.
His work carried out in the field of Control theory brings together such families of science as Control system, Compensation and Vibration control.
His most cited work include:
- Decentralized adaptive control of a class of large-scale interconnected nonlinear systems (209 citations)
- Decentralized adaptive output feedback design for large-scale nonlinear systems (151 citations)
- Dynamic high-gain scaling: State and output feedback with application to systems with ISS appended dynamics driven by all States (144 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Control theory, Control engineering, Nonlinear system, Adaptive control and Control theory.
Robust control, Robustness, Nonlinear control, Observer and Lyapunov function are the primary areas of interest in his Control theory study.
Farshad Khorrami usually deals with Control engineering and limits it to topics linked to Actuator and Vibration.
The concepts of his Nonlinear system study are interwoven with issues in Canonical form, Dual, Bounded function and System dynamics.
The Strict-feedback form research Farshad Khorrami does as part of his general Adaptive control study is frequently linked to other disciplines of science, such as Parametric statistics, therefore creating a link between diverse domains of science.
His Control theory research is multidisciplinary, relying on both Control system and Compensation.
He most often published in these fields:
- Control theory (66.67%)
- Control engineering (32.36%)
- Nonlinear system (31.39%)
What were the highlights of his more recent work (between 2013-2021)?
- Control theory (66.67%)
- Nonlinear system (31.39%)
- Artificial intelligence (10.68%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Control theory, Nonlinear system, Artificial intelligence, Control theory and Robustness.
His work on Nonlinear control as part of his general Control theory study is frequently connected to Dynamic scaling, thereby bridging the divide between different branches of science.
His Nonlinear system study combines topics from a wide range of disciplines, such as Observer, Integrator, State variable and System dynamics.
His studies in Artificial intelligence integrate themes in fields like Lidar, Machine learning and Computer vision.
Farshad Khorrami is interested in Adaptive control, which is a field of Control theory.
His Robustness research is multidisciplinary, incorporating perspectives in Adversarial system, Computer hardware, Unmanned ground vehicle, Anomaly detection and Hardware Trojan.
Between 2013 and 2021, his most popular works were:
- Cybersecurity for Control Systems: A Process-Aware Perspective (49 citations)
- Sensor modality fusion with CNNs for UGV autonomous driving in indoor environments (36 citations)
- Machine learning-based defense against process-aware attacks on Industrial Control Systems (31 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Electrical engineering
His main research concerns Artificial intelligence, Robustness, Nonlinear system, Control theory and Control system.
His research in Robustness intersects with topics in Lyapunov redesign and Mathematical optimization.
His Nonlinear system study combines topics in areas such as Forcing, State, Control engineering, Interval and System dynamics.
His study in the fields of Control theory under the domain of Control engineering overlaps with other disciplines such as Set.
His Control theory research is multidisciplinary, incorporating elements of Lyapunov function and Actuator.
His Control theory study frequently links to other fields, such as Integrator.
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