Papers
4
Total Citations
99
H-Index
3
About
A. Alessandri’s research centers on nonlinear system control, fault diagnosis, and mobile robotics, with a strong emphasis on integrating neural and Kalman filtering techniques for real-world applications. His most influential work, “Fault diagnosis for nonlinear systems using a bank of neural estimators” (2003, 60 citations), pioneered a robust framework for detecting and isolating faults in complex nonlinear dynamics, establishing a foundation for safety-critical autonomous systems. He further advanced adaptive control in “Adaptive neural network control of robotic manipulators” (2004, 20 citations), demonstrating how neural estimators can handle uncertainties in robotic motion. A landmark contribution to mobile robotics is “An application of the extended Kalman filter for integrated navigation in mobile robotics” (1997, 17 citations), which addressed the challenging problem of fusing gyro and wheel encoder data for dead reckoning in ground robots with nonlinear dynamics and sensors. More recently, Alessandri has explored electromagnetic actuation in “A Cost-Effective Integrated Methodology for Electromagnetic Actuation via Visual Feedback” (2024, 2 citations), proposing a low-cost visual feedback system to model and control complex electromagnetic forces. His work bridges theoretical rigor with practical implementation, impacting fields from robotics to biomedical engineering.
Research Focus
Key Achievements
Top Papers
- 1Fault diagnosis for nonlinear systems using a bank of neural estimators60 citations · 2003
- 2Adaptive neural network control of robotic manipulators20 citations · 2004
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