ICALEPCS 2025 Advanced Control Workshop

America/Chicago
Palmer House Hilton Chicago

Palmer House Hilton Chicago

17 East Monroe Street Chicago, IL 60603, United States of America
Daniel Tavares (CNPEM)
Description

The ICALEPCS 2025 Advanced Control Workshop gathered experts and beginners interested in sharing experiences and ideas on the application of control theory to real world feedback and feedforward systems, focusing on the optimization and stabilization of control loops (at design time or real time), applied system identification techniques, design of control architectures, autonomous decision systems, digital signal processing and hardware platforms where advanced control algorithms are implemented.

The talks recordings are now available at the ICALEPCS YouTube Channel.

The talks slides can be found in the Timetable page.

Feedback control systems are ubiquitous in large experimental physics facilities, from simple Proportional-Integral loops to layered control loops with multiple inputs and outputs, different sampling rates, high-order controllers, non-linear or time-varying plant responses, for which optimized performance is achieved based on system dynamics modeling. Many of such systems can operate fairly well with low tuning efforts, however a few others can largely benefit from a thorough system optimization rooted in control theory to provide relevant performance and robustness gains for the entire scientific facility.

In the ICALEPCS community, closed orbit or trajectory feedback systems, multibunch feedback systems, LLRF, fast power supplies, high performance timing systems, nanopositioning and other high dynamic mechatronic systems, plasma control, adaptive optics and radio telescope antenna control are the kind of systems typically requiring such advanced control techniques, but the list of applications may go far beyond due to the universality of the control techniques. System modeling, system identification, plant optimization, controller tuning, loop shaping,  robust control, adaptive control, nonlinear control, Model Predictive Control (MPC) and Iterative Learning Control (ILC) are only a few examples of such techniques.