Nader Meskin
Papers
13
Total Citations
121
H-Index
6
About
Nader Meskin is a prominent researcher whose work spans control systems, fault detection and isolation, and autonomous robotics — fields at the intersection of applied mathematics and intelligent systems engineering. He has made significant contributions to model reduction techniques for complex dynamical systems, notably developing a kernel-based principal component analysis approach for linear parameter-varying systems, which has attracted 37 citations and become a key reference in LPV model reduction. Meskin has also advanced data-driven methods for fault detection, leveraging deep neural networks and the Koopman operator to address sensor faults in nonlinear systems, earning 23 citations in just two years. A recurring theme throughout his research is fault-tolerant control for mobile robotics: his work on differential-drive robots employs multiple-model approaches, extended Kalman filters, and sliding mode controllers to ensure robust performance under actuator failures. More recently, he has extended this expertise to multi-robot coordination, autonomous docking with obstacle avoidance, and social robotics, reflecting a broadening vision toward real-world autonomous systems. With contributions spanning networked unmanned vehicles since 2008, Meskin has established a sustained and evolving research legacy that bridges theoretical control design and practical robotic implementation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7Actuator Fault Tolerant Control in a Team of Mobile Robots6 citations · 2018
- 8
- 9Fault Tolerant Controller Schemes for Single and Multiple Mobile Robots3 citations · 2020
- 10Social Robotics2 citations · 2023