A.G. Parlos

Papers

Total Citations

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About

A.G. Parlos is a researcher whose work centers on dynamic system identification and state estimation, with a particular focus on applying advanced filtering techniques to real-world engineering challenges. His major contributions lie in the development and refinement of parameter estimation methods for coupled dynamic systems, notably through the use of state estimate filters like the Extended Kalman Filter and Unscented Kalman Filter. In his most-cited work, "Parameter Estimation for Coupled Tank using Estimate Filtering" (2013), Parlos demonstrates how these filters—traditionally employed in robot and GPS navigation—can be effectively adapted to estimate parameters in dynamic systems, bridging a critical gap between theoretical control methods and practical industrial applications. While his citation count remains modest, his work provides foundational insights for researchers exploring nonlinear estimation in process control and fluid dynamics. Parlos’s research is particularly valuable for students and engineers seeking to understand how filtering techniques can be extended beyond navigation into broader dynamic system identification, offering a clear, applied perspective on complex estimation problems.