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Title: Extremum seeking x-ray position feedback using power line harmonic leakage as the perturbation

Abstract

Small x-ray beam sizes necessary for probing nanoscale phenomena require exquisite stability to prevent data corruption by noise. One source of instability at synchrotron radiation x-ray beamlines is the slow detuning of x-ray optics to marginal alignment where the onset of clipping increases the beam's susceptibility to higher frequency position oscillations. In this article, we show that a 1 mu m amplitude horizontal x-ray beam oscillation driven by power line harmonic leakage into the electron storage ring can be used as perturbation for horizontal position extremum seeking feedback. Feedback performance is characterized by convergence to 1.5% away from maximum intensity at optimal alignment.

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
National Institutes of Health (NIH)
OSTI Identifier:
1392125
DOE Contract Number:
AC02-06CH11357
Resource Type:
Journal Article
Resource Relation:
Journal Name: Physical Review Accelerators and Beams; Journal Volume: 19; Journal Issue: 9
Country of Publication:
United States
Language:
English

Citation Formats

Zohar, S., Kissick, D. J., Venugopalan, N., Ogata, C. M., Makarov, O., Stepanov, S., and Fischetti, R. F. Extremum seeking x-ray position feedback using power line harmonic leakage as the perturbation. United States: N. p., 2016. Web. doi:10.1103/PhysRevAccelBeams.19.092801.
Zohar, S., Kissick, D. J., Venugopalan, N., Ogata, C. M., Makarov, O., Stepanov, S., & Fischetti, R. F. Extremum seeking x-ray position feedback using power line harmonic leakage as the perturbation. United States. doi:10.1103/PhysRevAccelBeams.19.092801.
Zohar, S., Kissick, D. J., Venugopalan, N., Ogata, C. M., Makarov, O., Stepanov, S., and Fischetti, R. F. 2016. "Extremum seeking x-ray position feedback using power line harmonic leakage as the perturbation". United States. doi:10.1103/PhysRevAccelBeams.19.092801.
@article{osti_1392125,
title = {Extremum seeking x-ray position feedback using power line harmonic leakage as the perturbation},
author = {Zohar, S. and Kissick, D. J. and Venugopalan, N. and Ogata, C. M. and Makarov, O. and Stepanov, S. and Fischetti, R. F.},
abstractNote = {Small x-ray beam sizes necessary for probing nanoscale phenomena require exquisite stability to prevent data corruption by noise. One source of instability at synchrotron radiation x-ray beamlines is the slow detuning of x-ray optics to marginal alignment where the onset of clipping increases the beam's susceptibility to higher frequency position oscillations. In this article, we show that a 1 mu m amplitude horizontal x-ray beam oscillation driven by power line harmonic leakage into the electron storage ring can be used as perturbation for horizontal position extremum seeking feedback. Feedback performance is characterized by convergence to 1.5% away from maximum intensity at optimal alignment.},
doi = {10.1103/PhysRevAccelBeams.19.092801},
journal = {Physical Review Accelerators and Beams},
number = 9,
volume = 19,
place = {United States},
year = 2016,
month = 9
}
  • Small X-ray beam sizes necessary for probing nanoscale phenomena require exquisite stability to prevent data corruption by noise. One source of instability at synchrotron radiation X-ray beamlines is the slow detuning of X-ray optics to marginal alignment where the onset of clipping increases the beam’s susceptibility to higher frequency position oscillations. In this article, we show that a 1 µm amplitude horizontal X-ray beam oscillation driven by power line harmonic leakage into the electron storage ring can be used as perturbation for horizontal position extremum seeking feedback. Feedback performance is characterized by convergence to 1.5% away from maximum intensity atmore » optimal alignment.« less
  • Although proportional-integral-derivative (PID) controllers are widely used in the process industry, their effectiveness is often limited due to poor tuning. Manual tuning of PID controllers, which requires optimization of three parameters, is a time-consuming task. To remedy this difficulty, much effort has been invested in developing systematic tuning methods. Many of these methods rely on knowledge of the plant model or require special experiments to identify a suitable plant model. Reviews of these methods are given in [1] and the survey paper [2]. However, in many situations a plant model is not known, and it is not desirable to openmore » the process loop for system identification. Thus a method for tuning PID parameters within a closed-loop setting is advantageous. In relay feedback tuning [3]-[5], the feedback controller is temporarily replaced by a relay. Relay feedback causes most systems to oscillate, thus determining one point on the Nyquist diagram. Based on the location of this point, PID parameters can be chosen to give the closed-loop system a desired phase and gain margin. An alternative tuning method, which does not require either a modification of the system or a system model, is unfalsified control [6], [7]. This method uses input-output data to determine whether a set of PID parameters meets performance specifications. An adaptive algorithm is used to update the PID controller based on whether or not the controller falsifies a given criterion. The method requires a finite set of candidate PID controllers that must be initially specified [6]. Unfalsified control for an infinite set of PID controllers has been developed in [7]; this approach requires a carefully chosen input signal [8]. Yet another model-free PID tuning method that does not require opening of the loop is iterative feedback tuning (IFT). IFT iteratively optimizes the controller parameters with respect to a cost function derived from the output signal of the closed-loop system, see [9]. This method is based on the performance of the closed-loop system during a step response experiment [10], [11]. In this article we present a method for optimizing the step response of a closed-loop system consisting of a PID controller and an unknown plant with a discrete version of extremum seeking (ES). Specifically, ES is used to minimize a cost function similar to that used in [10], [11], which quantifies the performance of the PID controller. ES, a non-model-based method, iteratively modifies the arguments (in this application the PID parameters) of a cost function so that the output of the cost function reaches a local minimum or local maximum. In the next section we apply ES to PID controller tuning. We illustrate this technique through simulations comparing the effectiveness of ES to other PID tuning methods. Next, we address the importance of the choice of cost function and consider the effect of controller saturation. Furthermore, we discuss the choice of ES tuning parameters. Finally, we offer some conclusions.« less