Author: LeBlanc, G.
Paper Title Page
WEPPP057 Orbit Correction Studies using Neural Networks 2837
 
  • E. Meier, G. LeBlanc, Y.E. Tan
    ASCo, Clayton, Victoria, Australia
 
  This paper reports the use of Neural Networks for orbit correction at the Australian Synchrotron Storage Ring. The proposed system uses two Neural Networks in an actor-critic scheme to model a long term cost function and compute appropriate corrections. The system is entirely based on the history of the beam position and the actuators, the corrector magnets, in the storage ring. This makes the system auto-tuneable, which has the advantage of avoiding the use of a response matrix. As a generic and robust orbit correction program it can be used during commissioning and in slow orbit feedback. In this study, we present positive initial results of the simulations of the storage ring in Matlab. We will also discuss the possibility of reconstructing the response matrix from the information stored in the neural network for offline orbit response matrix analysis.