What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Electrical engineering
Thomas Parisini mostly deals with Control theory, Fault detection and isolation, Fault, Nonlinear system and Artificial neural network.
Control theory and Multi-agent system are frequently intertwined in his study.
The various areas that Thomas Parisini examines in his Fault detection and isolation study include Control engineering and Approximation theory.
His study in Fault is interdisciplinary in nature, drawing from both Fault tolerance, Distributed computing, Isolation and Key.
His Nonlinear system research incorporates elements of State variable and Residual.
His Radial basis function study, which is part of a larger body of work in Artificial neural network, is frequently linked to Field, bridging the gap between disciplines.
His most cited work include:
- A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems (493 citations)
- Adaptive fault-tolerant control of nonlinear uncertain systems: an information-based diagnostic approach (419 citations)
- Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation (274 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Control theory, Nonlinear system, Fault detection and isolation, Fault and Artificial neural network.
His studies deal with areas such as Bounded function and Feedforward neural network as well as Control theory.
His work carried out in the field of Nonlinear system brings together such families of science as Stability, Function, State and Residual.
The study incorporates disciplines such as Control engineering, Algorithm and Control reconfiguration in addition to Fault detection and isolation.
His Fault course of study focuses on Fault tolerance and Multi-agent system.
His Artificial neural network research is multidisciplinary, relying on both Stochastic approximation and Actuator.
He most often published in these fields:
- Control theory (71.22%)
- Nonlinear system (37.32%)
- Fault detection and isolation (31.22%)
What were the highlights of his more recent work (between 2018-2021)?
- Control theory (71.22%)
- Robustness (16.59%)
- Nonlinear system (37.32%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Control theory, Robustness, Nonlinear system, Distributed computing and Applied mathematics.
The concepts of his Control theory study are interwoven with issues in Telecommunications network and Control.
His work in Robustness covers topics such as Range which are related to areas like Platoon.
Thomas Parisini has researched Nonlinear system in several fields, including Real-time computing, Filter and Detector.
His work investigates the relationship between Distributed computing and topics such as Fault detection and isolation that intersect with problems in Control reconfiguration.
His work deals with themes such as Optimization problem, Nonlinear programming and Kernel, which intersect with Applied mathematics.
Between 2018 and 2021, his most popular works were:
- On Fast Multi-Shot COVID-19 Interventions for Post Lock-Down Mitigation (22 citations)
- On Fast Multi-Shot Epidemic Interventions for Post Lock-Down Mitigation: Implications for Simple Covid-19 Models. (20 citations)
- Plug-and-Play Fault Detection and Isolation for Large-Scale Nonlinear Systems With Stochastic Uncertainties (16 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Electrical engineering
His primary areas of study are Robustness, Control theory, Distributed computing, Amplitude and State observer.
His Robustness research incorporates themes from Feedback loop, Mobile agent, Open-loop controller and Transient.
His research in Control theory intersects with topics in Range, Phase and Record locking.
His Distributed computing study incorporates themes from Observer, Fault, Fault detection and isolation and Cyber-physical system.
His research investigates the connection with Fault and areas like Adaptive learning which intersect with concerns in Fault tolerance, Stability and Nonlinear system.
His Fault detection and isolation research is multidisciplinary, incorporating perspectives in Control reconfiguration, Residual, Kalman filter, Upper and lower bounds and Computation.
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