A Learning-Based Closed-Loop Fluid Flow Regulation
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.
Fields of Study & Subjects
Adaptive Control of Nonlinear Systems
Control Systems and Identification
Iterative Learning Control Systems
Publication details
- Journal / source
- Electronics
- Volume
- 15
- Issue
- 5
- Pages
- 953–953
- Publication date
- 26 February 2026
- Language
- EN