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Title: In-hardware demonstration of model-independent adaptive tuning of noisy systems with arbitrary phase drift

In this work, an implementation of a recently developed model-independent adaptive control scheme, for tuning uncertain and time varying systems, is demonstrated on the Los Alamos linear particle accelerator. The main benefits of the algorithm are its simplicity, ability to handle an arbitrary number of components without increased complexity, and the approach is extremely robust to measurement noise, a property which is both analytically proven and demonstrated in the experiments performed. We report on the application of this algorithm for simultaneous tuning of two buncher radio frequency (RF) cavities, in order to maximize beam acceptance into the accelerating electromagnetic field cavities of the machine, with the tuning based only on a noisy measurement of the surviving beam current downstream from the two bunching cavities. The algorithm automatically responds to arbitrary phase shift of the cavity phases, automatically re-tuning the cavity settings and maximizing beam acceptance. Because it is model independent it can be utilized for continuous adaptation to time-variation of a large system, such as due to thermal drift, or damage to components, in which the remaining, functional components would be automatically re-tuned to compensate for the failing ones. We start by discussing the general model-independent adaptive scheme and howmore » it may be digitally applied to a large class of multi-parameter uncertain systems, and then present our experimental results.« less
Authors:
 [1] ;  [1] ;  [1] ;  [1] ;  [1]
  1. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Publication Date:
OSTI Identifier:
1193396
Report Number(s):
LA-UR--14-21532
Journal ID: ISSN 0168-9002; PII: S0168900214004227
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment
Additional Journal Information:
Journal Volume: 756; Journal Issue: C; Journal ID: ISSN 0168-9002
Publisher:
Elsevier
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; 97 MATHEMATICS AND COMPUTING; 43 PARTICLE ACCELERATORS linac; adaptive control; feedback control; model independent control; RF cavity; phase drift