Intelligent Agent Based Operator Support and Beam Orbit Control Scheme for Synchrotron Radiation Sources

Synchrotron radiation (SR) sources provide very high photon flux light in a very narrow opening angle with wavelength ranging from visible to hard X-rays for use in experiments related to material science, physics, chemistry and biology. In the beam lines (BL) the SR position is highly dependent on the electron beam position and angle at the source point. The tuning of accelerator for getting the desired electron beam position and angle at the source point is a time consuming and regular job done during commissioning of new BL or when accelerator is operated at new operating point. This paper presents a novel intelligent agent based operator support and beam orbit control scheme for accelerator control. The proposed multi-agent based scheme is well suited for the multilayer control system architectures of synchrotron radiation sources. The scheme successfully distributes the orbit control job to multiple low complexity reactive agents that work simultaneously and control the local orbit for individual BL and insertion devices (ID) in an optimized manner. The proposed scheme of beam orbit control in particular is very useful for machines like INDUS2, where new BL are in the process of commissioning as this scheme reduces the operator efforts and accelerator tuning time for providing beam to new BL. It also extends the beam availability to other BL (already installed and in use) as the agent tunes the accelerator in systematic way and under constraints on local orbit bump leakage thereby enabling the use of other BL for routine experiments which otherwise was not possible. The effectiveness of the scheme is shown through simulation results obtained by applying the stated scheme on INDUS-2 storage ring model.

[1]  C. Stern,et al.  A Control System for Accelerator Tuning Combining Adaptive Plan Execution with Online Learning , 2022 .

[2]  Sheng Gehao,et al.  Optimal Coordination For Multi-Agent Based Secondary Voltage Control In Power System , 2005, 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific.

[3]  W. Herr Algorithms and procedures used in the orbit correction package COCU {Closed Orbit Correction Utilities) , 1995 .

[4]  Gwyn Morgan,et al.  The Application of Multi-Agent Systems to the Design of an Intelligent Geometry Compressor , 2002 .

[5]  H. Lancaster,et al.  Advanced Light Source control system , 1989, Proceedings of the 1989 IEEE Particle Accelerator Conference, . 'Accelerator Science and Technology.

[6]  Satoshi Yamaguchi,et al.  Reinforcement learning using a stochastic gradient method with memory‐based learning , 2010 .

[7]  Jongeun Choi,et al.  Cooperatively learning mobile agents for gradient climbing , 2007, 2007 46th IEEE Conference on Decision and Control.

[8]  Peter L. Bartlett,et al.  Infinite-Horizon Policy-Gradient Estimation , 2001, J. Artif. Intell. Res..

[9]  Francisco P. Maturana,et al.  Agent virtual machine for automation controllers , 2008 .

[10]  Daniel Marcu,et al.  Foundations of a Logical Approach to Agent Programming , 1995, ATAL.

[11]  Kwang Y. Lee,et al.  Implementation of a multi-agent system for optimized multiobjective power plant control , 2010, North American Power Symposium 2010.

[12]  Yufeng Mo,et al.  A Navigation System Based on Subsumption Architecture , 2010, 2010 International Conference on Measuring Technology and Mechatronics Automation.

[13]  E. Weckert,et al.  Review of third and next generation synchrotron light sources , 2005 .

[14]  Sandip Sen,et al.  MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions , 2008, AAMAS.

[15]  P. V. Varde,et al.  Model-based tracking for agent-based control systems in the case of sensor failures , 2012, Int. J. Autom. Comput..

[16]  R. C. Barrett Accelerator Physics , 1970, Nature.

[17]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[18]  A. K. Majumder,et al.  International Journal of Advanced Science and Technology , 2013 .

[19]  H. Wiedemann Particle accelerator physics , 1993 .