Abstract: The goal and task of intelligent fully mechanized working face are to independently complete the reliable coal cutting of the fully mechanized working face, maintain the geometric relationship of the working face and reliable roof support. According to the goal and task, the key technologies of intelligent control of fully mechanized working face are proposed. The technologies include shearer positioning technology, working face visualization technology, hydraulic support electro-hydraulic control technology (device), working face communication technology, collaborative control technology of fully mechanized mining equipment, autonomous height adjustment technology of shearer, autonomous straightening technology of working face and surrounding rock support control technology of working face. Among these technologies, the first three technologies belong to the perception and execution layer of intelligent fully mechanized working face. The working face communication technology is the transmission layer of intelligent fully mechanized working face. And the last four technologies belong to the decision-making layer of intelligent fully mechanized working face. The challenges faced by the intelligent fully mechanized working face are pointed out, which are that the autonomous decision-making capability of the decision-making layer cannot adapt to the complex and changeable working conditions, and the perception and execution layer cannot support the information demand of the decision-making layer and the reliable execution of the decision-making instructions. In order to solve the above challenges, the digital twin system architecture of fully mechanized working face is proposed by use of the simulation-based digital twin modeling method. The virtual entity of the digital twin system of the fully mechanized working face comprises a mechanism model and a behavior model. The unmeasurable data of a physical system of the fully mechanized working face equipment can be obtained by the mechanism model. The behavior model can provide holographic information reflecting the running state of the physical equipment for an intelligent control system of the fully mechanized working face. Thus the problem of the lack of data information in the decision-making layer is solved. The off-line run mode of the combination of the mechanism model of fully mechanized mining equipment and its control system forms the hardware in the loop simulation system of fully mechanized working face, which provides a test platform for intelligent control algorithms based on process rules. The off-line run mode of the combination of the mechanism model, behavior model and its control system of the fully mechanized mining equipment forms the calculation experimental system of the fully mechanized working face, which provides a test platform for the development of the real independent decision-making complex algorithm of the intelligent control system of the fully mechanized working face.