ICALEPCS2019 - List of Authors (Brown, K.A.)

Paper	Title	Page
MOPHA043	Accelerator Control Data Mining with WEKA	293
	W. Fu, K.A. Brown, T. D’Ottavio, P.S. Dyer, S. Nemesure BNL, Upton, New York, USA
	Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. Accelerator control systems generates and stores many time-series data related to the performance of an accelerator and its support systems. Many of these time series data have detectable change trends and patterns. Being able to timely detect and recognize these data change trends and patterns, analyse and predict the future data changes can provide intelligent ways to improve the controls system with proactive feedback/forward actions. With the help of advanced data mining and machine learning technology, these types of analyses become easier to produce. As machine learning technology matures with the inclusion of powerful model algorithms, data processing tools, and visualization libraries in different programming languages (e.g. Python, R, Java, etc), it becomes relatively easy for developers to learn and apply machine learning technology to online accelerator control system data. This paper explores time series data analysis and forecasting in the Relativistic Heavy Ion Collider (RHIC) control systems with the Waikato Environment for Knowledge Analysis (WEKA) system and its Java data mining APIs.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA043
About •	paper received ※ 20 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020
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MOPHA045	A New Simulation Stucture to Improve Software Dependability in Collider-Accelerator Control Systems	301
	Y. Gao, T.G. Robertazzi Stony Brook University, Stony Brook, New York, USA K.A. Brown, J. Morris, R.H. Olsen BNL, Upton, New York, USA
	In this work, we propose a new simulation framework aiming to improve the robustness of the control system. It focuses on enhancing the reliability of controls ADO codes by running user-customized testing. The new simulation architecture has two independent parts; together they cover a large amount of ADOs frequently used by developers. The first part of the simulation framework focuses on testing ADOs with GPIB connections to devices. It consists of several function blocks and has a switch mechanism which enables users to conveniently turn on and off the simulation mode without changing the ADO codes. Moreover, it contains a special module which automates testing on ADO codes. Testing results are summarized and presented to users for codes analysis. The second part of the framework adopts a totally different structure. It simulates a different type of interface. Specifically, it focuses on testing ADOs with Ethernet connections to devices. It is based on a powerful networking engine called Twisted, which is an event-driven network programming framework developed by the Twisted Matrix Labs. The simulation framework can handle multiple types of devices at the same time.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA045
About •	paper received ※ 27 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA046	A New Simulation Timing System for Software Testing in Collider-Accelerator Control Systems	307
	Y. Gao, T.G. Robertazzi Stony Brook University, Stony Brook, New York, USA K.A. Brown, M. Harvey, J. Morris, R.H. Olsen BNL, Upton, New York, USA
	Particle accelerators need a timing mechanism to properly accelerate the beam from its source to its destination. The synchronization among accelerator devices is important, which is accomplished by a distribution of timing signals. Devices which require their times synchronized to the acceleration cycle are connected to timelines. Timing signals are sent out along the timelines in the form of digital codes. Correspondingly, devices in the complex are equipped with timeline decoders, which allow devices to extract timing signals appropriately. In this work, a new simulation architecture is introduced which can generate user-specific timing events for software testing in the control systems.
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA046
About •	paper received ※ 27 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUCPL07	Optimal Control for Rapid Switching of Beam Energies for the ATR Line at BNL	789
	J.P. Edelen, N.M. Cook RadiaSoft LLC, Boulder, Colorado, USA K.A. Brown, P.S. Dyer BNL, Upton, New York, USA
	Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Award Number DE-SC0019682. The Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory will undergo a beam energy scan over the next several years. To execute this scan, the transfer line between the Alternating Gradient Synchrotron (AGS) and RHIC or the so-called the ATR line, must be re-tuned for each energy. Control of the ATR line has four primary constraints: match the beam trajectory into RHIC, match the transverse focusing, match the dispersion, and minimize losses. Some of these can be handled independently, for example orbit matching. However, offsets in the beam can affect the transverse beam optics, thereby coupling the dynamics. Furthermore, the introduction of vertical optics increases the possibilities for coupling between transverse planes, and the desire to make the line spin transparent further complicates matters. During this talk, we will explore three promising avenues for controlling the ATR line, model predictive control (MPC), on-line optimization methods, and hybrid MPC and optimization methods. We will provide an overview of each method, discuss the tradeoffs between these methods, and summarize our conclusions.
	Slides TUCPL07 [4.459 MB]
DOI •	reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-TUCPL07
About •	paper received ※ 08 October 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020
Export •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Accelerator Control Data Mining with WEKA

293

W. Fu, K.A. Brown, T. D’Ottavio, P.S. Dyer, S. Nemesure
BNL, Upton, New York, USA

Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy.
Accelerator control systems generates and stores many time-series data related to the performance of an accelerator and its support systems. Many of these time series data have detectable change trends and patterns. Being able to timely detect and recognize these data change trends and patterns, analyse and predict the future data changes can provide intelligent ways to improve the controls system with proactive feedback/forward actions. With the help of advanced data mining and machine learning technology, these types of analyses become easier to produce. As machine learning technology matures with the inclusion of powerful model algorithms, data processing tools, and visualization libraries in different programming languages (e.g. Python, R, Java, etc), it becomes relatively easy for developers to learn and apply machine learning technology to online accelerator control system data. This paper explores time series data analysis and forecasting in the Relativistic Heavy Ion Collider (RHIC) control systems with the Waikato Environment for Knowledge Analysis (WEKA) system and its Java data mining APIs.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA043

About •

paper received ※ 20 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA045

A New Simulation Stucture to Improve Software Dependability in Collider-Accelerator Control Systems

301

Y. Gao, T.G. Robertazzi
Stony Brook University, Stony Brook, New York, USA
K.A. Brown, J. Morris, R.H. Olsen
BNL, Upton, New York, USA

In this work, we propose a new simulation framework aiming to improve the robustness of the control system. It focuses on enhancing the reliability of controls ADO codes by running user-customized testing. The new simulation architecture has two independent parts; together they cover a large amount of ADOs frequently used by developers. The first part of the simulation framework focuses on testing ADOs with GPIB connections to devices. It consists of several function blocks and has a switch mechanism which enables users to conveniently turn on and off the simulation mode without changing the ADO codes. Moreover, it contains a special module which automates testing on ADO codes. Testing results are summarized and presented to users for codes analysis. The second part of the framework adopts a totally different structure. It simulates a different type of interface. Specifically, it focuses on testing ADOs with Ethernet connections to devices. It is based on a powerful networking engine called Twisted, which is an event-driven network programming framework developed by the Twisted Matrix Labs. The simulation framework can handle multiple types of devices at the same time.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA045

About •

paper received ※ 27 September 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

MOPHA046

A New Simulation Timing System for Software Testing in Collider-Accelerator Control Systems

307

Y. Gao, T.G. Robertazzi
Stony Brook University, Stony Brook, New York, USA
K.A. Brown, M. Harvey, J. Morris, R.H. Olsen
BNL, Upton, New York, USA

Particle accelerators need a timing mechanism to properly accelerate the beam from its source to its destination. The synchronization among accelerator devices is important, which is accomplished by a distribution of timing signals. Devices which require their times synchronized to the acceleration cycle are connected to timelines. Timing signals are sent out along the timelines in the form of digital codes. Correspondingly, devices in the complex are equipped with timeline decoders, which allow devices to extract timing signals appropriately. In this work, a new simulation architecture is introduced which can generate user-specific timing events for software testing in the control systems.

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA046

About •

paper received ※ 27 September 2019 paper accepted ※ 08 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUCPL07

Optimal Control for Rapid Switching of Beam Energies for the ATR Line at BNL

789

J.P. Edelen, N.M. Cook
RadiaSoft LLC, Boulder, Colorado, USA
K.A. Brown, P.S. Dyer
BNL, Upton, New York, USA

Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Award Number DE-SC0019682.
The Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory will undergo a beam energy scan over the next several years. To execute this scan, the transfer line between the Alternating Gradient Synchrotron (AGS) and RHIC or the so-called the ATR line, must be re-tuned for each energy. Control of the ATR line has four primary constraints: match the beam trajectory into RHIC, match the transverse focusing, match the dispersion, and minimize losses. Some of these can be handled independently, for example orbit matching. However, offsets in the beam can affect the transverse beam optics, thereby coupling the dynamics. Furthermore, the introduction of vertical optics increases the possibilities for coupling between transverse planes, and the desire to make the line spin transparent further complicates matters. During this talk, we will explore three promising avenues for controlling the ATR line, model predictive control (MPC), on-line optimization methods, and hybrid MPC and optimization methods. We will provide an overview of each method, discuss the tradeoffs between these methods, and summarize our conclusions.

Slides TUCPL07 [4.459 MB]

DOI •

reference for this paper ※ https://doi.org/10.18429/JACoW-ICALEPCS2019-TUCPL07

About •

paper received ※ 08 October 2019 paper accepted ※ 10 October 2019 issue date ※ 30 August 2020

Export •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)