Abstract: Due to its high complexity and multiple influencing factors, traditional automatic control technology is difficult to ensure the autonomous, reliable, and efficient operation of large astronomical optical telescopes. Therefore, there is an urgent need to improve the reliability and observation quality of telescopes. This study constructs a control system supported by a new generation of artificial intelligence technology through the organic integration of deep learning, intelligent agents, and other technologies. With the support of an artificial intelligence software experimental platform, the development of two application control systems, reliability management and observation quality optimization, has been achieved. These two application systems will run on historical data from LAMOST (Large Sky Area Multi-Object Fiber Spectroscopic Telescope) and be validated and evaluated through simulation. The research results will provide pioneering research for the intelligent development of existing and next-generation telescope control systems in China.