HB2014 - List of Authors (Rock, S.M.)

Paper	Title	Page
MOPAB24	Identification of Intra-bunch Transverse Dynamics for Feedback Control Purposes at CERN Super Proton Synchrotron	79
	O. Turgut, J.D. Fox, C.H. Rivetta SLAC, Menlo Park, California, USA W. Höfle CERN, Geneva, Switzerland S.M. Rock Stanford University, Stanford, California, USA
	Funding: Work supported by the U.S. Department of Energy under contract DE-AC02-76SF00515 and the US LHC Accelerator Research Program (LARP). We present methods for parameter estimation of intra-bunch transverse beam dynamics. The dynamics is represented via reduced order linear models. These models are useful in beam monitoring and in the design of feedback controllers to stabilize intra-bunch transverse instabilities. The effort is motivated by the plans to increase currents in the Super Proton Synchrotron as part of the HL-LHC upgrade where feedback methods could control instabilities and allow greater freedom in machine lattice parameters. Identification algorithms use subspace methods to compute a discrete multi-input multi-output (MIMO) representation of the nonlinear dynamics. We use macro particle simulation data (CMAD and HEADTAIL) and SPS machine measurements as the source of dynamics information for the identification of beam dynamics. Reduced models capture the essential dynamics of the beam motion or instability at a particular operating point, and can then be used analytically to design optimal feedback controllers. The robustness of the model parameters against noise and external excitation signals is studied, as is the effect of the MIMO model order on the accuracy of the identification algorithms.

Paper

Title

Page

Identification of Intra-bunch Transverse Dynamics for Feedback Control Purposes at CERN Super Proton Synchrotron

79

O. Turgut, J.D. Fox, C.H. Rivetta
SLAC, Menlo Park, California, USA
W. Höfle
CERN, Geneva, Switzerland
S.M. Rock
Stanford University, Stanford, California, USA

Funding: Work supported by the U.S. Department of Energy under contract DE-AC02-76SF00515 and the US LHC Accelerator Research Program (LARP).
We present methods for parameter estimation of intra-bunch transverse beam dynamics. The dynamics is represented via reduced order linear models. These models are useful in beam monitoring and in the design of feedback controllers to stabilize intra-bunch transverse instabilities. The effort is motivated by the plans to increase currents in the Super Proton Synchrotron as part of the HL-LHC upgrade where feedback methods could control instabilities and allow greater freedom in machine lattice parameters. Identification algorithms use subspace methods to compute a discrete multi-input multi-output (MIMO) representation of the nonlinear dynamics. We use macro particle simulation data (CMAD and HEADTAIL) and SPS machine measurements as the source of dynamics information for the identification of beam dynamics. Reduced models capture the essential dynamics of the beam motion or instability at a particular operating point, and can then be used analytically to design optimal feedback controllers. The robustness of the model parameters against noise and external excitation signals is studied, as is the effect of the MIMO model order on the accuracy of the identification algorithms.