  In order to improve the stability of synchrotron radiation, we developed a
new method of machine learning-based closed orbit feedback and piloted it in
the storage ring of the Shanghai Synchrotron Radiation Facility (SSRF). In our
experiments, not only can the machine learning-based closed orbit feedback
carry out horizontal, vertical and RF frequency feedback simultaneously, but it
also has better convergence and convergence speed than the traditional Slow
Orbit Feed Back (SOFB) system. What's more, the residual values of the
correctors' currents variations after correction can be almost ignored. This
machine learning-based new method is expected to establish a new closed orbit
feedback system and improve the orbit stability of the storage ring in daily
operation.
