Author: Safranek, J.A.
Paper Title Page
TUPWO064 Online Optimization Algorithms for Accelerators and Experimental Results 2012
  • X. Huang, W.J. Corbett, J.A. Safranek, J. Wu
    SLAC, Menlo Park, California, USA
  Online optimization of accelerators is becoming increasingly more important as accelerator systems become more and more complex. Online accelerator optimization is generally a multi-variant nonlinear problem with considerable noise. Efficiency and robustness are critical for online applications. Therefore optimization algorithms require special considerations. In this study we evaluate the viability of several online optimization algorithms for both ring and linac machines. Numerical simulations and experimental tests are presented to investigate performance of the algorithms.