Control System Cybersecurity
Hyperlink: https://indico.cern.ch/event/1487380/
Organizer: Stefan Lueders (CERN)
Date: Sunday 9/21/2025
Duration: Full-day
Description: Attacks against industrial control systems, including Ransomware and politically motivated attacks, are now regularly reported in the media; new vulnerabilities are regularly published and exploited; and politicians become more and more concerned about the resilience of the control systems controlling a nation’s critical infrastructure. Modern accelerator and detector control systems do not differ significantly from the control systems used in industry or devices being part of the “Internet-of-Things” (IoT). Modern Information Technologies (IT) are commonly used, control systems are based more and more on common-of-the-shelf hardware/software (VME, PLCs, VxWorks, network switches, networked controls hardware, SCADA, commercial middleware, etc.) or Windows/Linux PCs, and commonly employ standard IT-techniques (Git & built frameworks, virtualisation & containerisation, Machine Learning, etc.). Furthermore, due to the academic freedom in the High Energy Physics community, control systems are produced in a wide, decentralized community, which leads to heterogeneous systems and often necessitates remote access. However, with this adoption of modern IT standards, control systems are also exposed to the inherent vulnerabilities of the corresponding hardware and software. The consequences of a security breach in an accelerator or detector control system might be severe, and attackers won’t ignore High Energy Physics (HEP) systems just because it’s HEP.
Bluesky
Organizer: Eric Codrea (ANL)
Date: Sunday 9/21/2025
Duration: Full-day
Description: The Bluesky framework is an innovative suite of open-source software tools, libraries, and applications developed collaboratively to revolutionize the way scientific data is acquired and accessed. The Bluesky Data Acquisition & Data Access Workshop offers an ideal forum for data scientists, developers, and project managers to come together, share best practices, and discuss emerging solutions. Participants will gain insight into current projects at leading laboratories, explore enhancements to existing systems, and collaborate on new strategies to improve data utility and foster community-wide progress.
Motion Control and Robotics
Organizer: Tentative at this time.
Date: Sunday 9/21/2025
Duration: Full-day
Description: Tentative at this time.
Advancing AI/ML and Generative Models for the Control of Large Complex Systems
Organizer: Alex Scheinker (LANL)
Date: Sunday 9/21/2025
Duration: Full-day
Description: Join us for an insightful and hands-on workshop on Artificial Intelligence (AI) and Machine Learning (ML), where you will explore the fundamental concepts, tools, and techniques shaping the future of technology. The first part of the workshop is designed to provide participants with a strong understanding of AI/ML principles, ranging from data preprocessing and model selection to evaluating algorithms and deploying AI solutions. The second part is focused on generative AI that has emerged as a transformational technology impacting all fields of science and engineering.
The workshop will include talks that explore various ongoing efforts to use AI/ML and generative AI for the control of large complex systems including examples such as particle accelerators and X-ray imaging at light sources. The workshop will provide several tutorials on the current state-of-the-art in AI/ML techniques including foundations of the AI tools. The workshop will also discuss many of the existing challenges of AI and what needs to be done in the future. For example, despite its many successes, two of the major challenges faced by AI tools, which limits their use for real-time control of complex systems are: 1) a lack of physics constraints and 2) a lack of robustness for time-varying systems for which they rely on brute force re-training. The workshop will explore how hard physics constraints are being incorporated into the architectures of generative models and how adaptive feedback is being used in generative models to make them more robust.
We invite participants to actively contribute their insights, experiences, and questions throughout the workshop, fostering an engaging and collaborative environment for exploring the cutting-edge advancements in AI/ML and generative models.
Advanced Control
Hyperlink: https://indico.cnpem.br/e/iacow2025
Organizer: Daniel Tavares (LNLS)
Date: Sunday 9/21/2025
Duration: Half-day
Description: 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 optimization rooted in control theory to provide relevant performance and robustness gains for the entire scientific facility.
The ICALEPCS Advanced Control Workshop gathers 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. Discussions about the interplay between the control science and artificial intelligence are also encouraged.
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.
The workshop will last half day and will consist of talks contributed by the community and discussion sessions.Feedback control systems are ubiquitous in large experimental physics facilities, from simple PI (Proportional-Integral) loops to layered control loops with multiple inputs and outputs, different sampling rates, high-order controllers, non-linear or time-varying behaviors, 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 other can largely benefit from a thorough optimization rooted in control theory to provide relevant performance and robustness gains to the facility.
The ICALEPCS Advanced Control Workshop gathers experts and beginners interested in sharing experiences and ideas on the application of control theory to real world feedback and feed-forward systems, focusing on the optimization and stabilization of control loops (at design time or real time), applied system identification techniques, design of control architectures and autonomous decision. Discussions about the interplay of the control science with artificial intelligence are also encouraged.
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 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.
The workshop will consist of talks contributed by the community and discussion sessions.
Safety Lessons Learned
Organizer: Barry Fischler (SLAC)
Date: Sunday 9/21/2025
Duration: Half-day
Description: Join this collaborative workshop featuring a series of lightning talks from attendees on personnel safety and machine protection incidents, along with the valuable lessons learned. Controls play a pivotal role in ensuring safety across our facilities, and it’s in everyone’s best interest to learn from both our mistakes and improvements. We highly encourage all attendees to submit an abstract followed by a brief presentation, though it is not mandatory. Each presentation will be followed by a brief Q&A period, providing a great opportunity for interactive learning and discussion. Don’t miss out on this chance to share your experiences and gain insights from your peers.
