Accelerator and feedback control simulation using neural networks

Neural networks can adapt as the dynamics of a process changes with time. Using a process model, the accelerator network is first trained to simulate the dynamics of the beam for a given beam line. This accelerator network is then used to train a second controller network which performs the control function. In simulation, the networks are used to adjust corrector magnets to control the launch angle and position of the beam to keep it on the desired trajectory when the incoming beam is perturbed.<>