Abstract: Shearer is the core equipment of fully mechanized mining face. Under some complex coal seam conditions, the working conditions of shearer are harsh, the environment is complex, and the mining equipment is not very intelligent. Those have led to many coal mining disasters, and the poor adaptability, high failure rate and low efficiency of shearer. Improving the reliability and adaptability of coal mining equipment is one of the main tasks for the intelligent development of coal mines. The coupling mechanism between the working mechanism of shearer and the complex coal seam, and the guidance and control mechanism of the cutting state of coal and rock and the power transmission system are the keys to realize the intelligent and efficient cutting of shearer. Based on virtual prototype technology, fuzzy control technology, combined with data adaptive weighted fusion algorithm and deep reinforcement learning algorithm, the method of combining multi-domain modeling with collaborative simulation and experimental analysis is used to build a machine-electric-hydraulic control integrated self adaptive cutting system model for shearer and investigate the self-adaptive cutting control strategy of shearer. The AMEsim is used to build a height-adjusting hydraulic system model which integrates with the EDEM-RecurDyn coal and rock cutting bi-directional coupling model. According to the actual occurrence conditions of coal seams, the range of coal rock solidity coefficient grades is divided. Aiming to optimize the overall performance of shearer, the improved MOGWO algorithm is used to optimize the traction speed and drum speed of shearer. The time-domain vibration signal of the shearer cutting part is used as the characteristic parameter of coal and rock cutting state recognition, and the data adaptive weighted fusion algorithm is used for fusion processing. Based on the fusion value of characteristic parameters, the fuzzy control is used to realize the intelligent recognition of the cutting state of coal and rock. Using Simulink, a shearer traction speed-drum speed (vq-n) coordinated speed regulation and self-adaptive height control system model is built based on the DDPG. Using the interface technology to realize EDEM-RecurDyn-AMEsim-Simulink coupling, a machine-electric hydraulic-control integrated shearer self-adaptive cutting control system model is constructed and the simulation is performed. The research results show that the system takes the coal and rock cutting simulation data stream as the main focus, and can realize the perceptual analysis of the coal and rock cutting dynamic process, signal feature processing and self-adaptive adjustment decision-making control. Physical experiments are used to verify the feasibility and reliability of the results based on the EDEM-Recur Dyn coupling simulation. Under the premise of ensuring the optimal overall performance of the shearer and its dynamic reliability, when the spiral drum is located at the upper position and the firmness coefficient of coal and rock mass f>7 is identified, the vq-n cooperative speed regulation and adaptive height regulation control strategy are adopted according to the working conditions of cutting the roof by the drum. According to the variation trend of vibration acceleration fluctuation in the direction of drum cutting resistance within the sampling time (2 s) during the height adjustment process, it can be further assessed whether it is in the state of cutting the roof, cutting the hard coal and rock or hard nodules (f>7 and not the top and bottom plate). If the identification result is the latter or the firmness coefficient of coal and rock mass f≤7, only the vq-n cooperative speed regulation strategy is adopted. When the coal and rock mass firmness coefficient f value is reduced, the selection of the vq-n simultaneous control strategy can fully consider the performance indicators of the shearer. When the coal and rock mass firmness coefficient f value is increased, in order to ensure the dynamic reliability of the shearer, the sequential control strategy in which the traction speed takes precedence over the drum speed is selected. Compared with the simultaneous control strategy, the drum load can be reduced by 23.7% and the load fluctuation can be reduced by 28.1%. The simulation process verifies that the system can accurately adjust the shearer traction speed, drum speed and drum height according to the expected control strategy. The change in cutting conditions can be sensed after only 0.64 s, and the adjustment is real-time showing a rapidity of response. The technology realizes the shearer self adaptive cutting under complex coal seam conditions. The study verifies the correctness of the built shearer self-adaptive cutting control system and simulation results through physical tests, which can effectively improve the shearer’s adaptability to operate in complex coal seams.