A Learning-Based Closed-Loop Fluid Flow Regulation
Year: 2026
Type: article
Abstract: This paper presents a learning-based robust control strategy for fluid flow dynamic systems, designed to compensate for modeling uncertainties and unknown disturbances inherent to closed-loop active flow control applications. The method is grounded in nonlinear control theory and uses gradient descent learning rules to continuously update control parameters and disturbance estimate. The resulting closed-loop system achieves robust regulation while maintaining simplicity and interpretability in both implementation and analysis. Numerical simulations are conducted to validate the approach.
Source: Electronics
Authors: Mahmut Reyhanoglu, Mohammad Jafari
Institutions: Wentworth Institute of Technology, Columbus State University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7131676799