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In order to improve the stability of synchrotron radiation, we developed anew method of machine learning-based closed orbit feedback and piloted it inthe storage ring of the Shanghai Synchrotron Radiation Facility (SSRF). In ourexperiments, not only can the machine learning-based closed orbit feedbackcarry out horizontal, vertical and RF frequency feedback simultaneously, but italso has better convergence and convergence speed than the traditional SlowOrbit Feed Back (SOFB) system. What's more, the residual values of thecorrectors' currents variations after correction can be almost ignored. Thismachine learning-based new method is expected to establish a new closed orbitfeedback system and improve the orbit stability of the storage ring in dailyoperation.

A machine-learning based closed orbit feedback for the SSRF storage ring