Laurinda L. N. dos Reis
Papers
5
Total Citations
86
H-Index
3
About
Laurinda L. N. dos Reis is a robotics researcher whose work focuses on advancing the control and identification of robotic manipulators for industrial applications. Her research spans system identification, controller design, and machine learning techniques for robotic systems. Her most cited work, "Identification by Recursive Least Squares With Kalman Filter (RLS-KF) Applied to a Robotic Manipulator" (2021, 41 citations), introduces a novel hybrid approach that combines recursive least squares with Kalman filtering for improved system identification, enabling more accurate model outputs that closely match real system behavior. She has also made significant contributions to controller comparison and optimization, as demonstrated in her paper comparing PID and LQR controllers (2019, 21 citations) and her work on PID controller optimization using particle swarm optimization (2021, 20 citations). Her research addresses the growing industrial demand for more efficient and precise robotic control systems. Through her comparative studies of classical and modern control strategies, dos Reis provides valuable insights for engineers seeking to optimize robotic manipulator performance in production environments. Her work continues to influence the development of more sophisticated control architectures for industrial robotics.
Research Focus
Key Achievements
Top Papers
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- 3PID controller with novel PSO applied to a joint of a robotic manipulator20 citations · 2021
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