LPA Online Workshop on Control Systems and Machine Learning

Sitzung

Poster session A Room 1

24.01.2022, 18:30

1. Challenges in automating experimental setups

Nicole Wagner

24.01.22, 18:30

Experimental scientists have always a need for high flexibility in realizing their setups. That poses a huge challenge for the engineers who try to catch up and have the goal to minimize the variety of devices or to standardize the interfaces between the components. This area of conflict mostly covers motion tasks, machine safety and environmental conditioning.
This talk touches some of the...

9. Tango Controls as control system for a university high power laser lab

Nils Weiße (CALA), Leonard Doyle (LMU), Faran Irshad (CALA-LMU Munich)

24.01.22, 18:40

Tango Controls has been adopted as main system for supervisory control and data acquisition at the Center for Advanced Laser Applications (CALA) in recent years. As an open-source, free and software independent toolkit it is highly customizable and applicable for almost any measurement device. In its current implementation at CALA the main laser system, as well as each experimental cave, has...

10. Current design of the data acquisition system at the Centre for Advanced Laser Applications (CALA)

Herr Leonard Doyle (LMU)

24.01.22, 18:50

The Centre for Advanced Laser Applications (CALA) in Munich is home to the ATLAS-3000 high power laser dedicated to research on laser particle acceleration and applications thereof. The laser and each experimental area are running control systems based on Tango controls. In addition to the hardware control, this is used to record experimental data in an automated fashion with every laser shot....

22. Studies on Reinforcement Learning Applications for Accelerator Optimization and Control

Oliver Stein (DESY), Herr Jan Kaiser (DESY)

24.01.22, 19:05

In recent research, reinforcement learning algorithms have been shown capable of solving complex control tasks, also showing potential for beam control, and in the optimization and automation of tasks in accelerator operation.
As part of the Helmholtz AI project "Machine Learning Toward Autonomous Accelerators" -- a collaboration between DESY and KIT -- reinforcement learning applications...