RESUMO
Emulsion pump station is widely used to provide power for full-mechanized coal mining face equipment. With the development of the mining technique of longwall face and the extensive use of large mining height and high working resistance of the hydraulic support, the fluid supply pressure is more unstable and the pressure impact is increasingly intensified. The intelligent control of the emulsion pump station is the key to the development of the stable fluid supply technology at the working face. This paper develops a new on-line adaptive learning technique to improve the response speed of pumping station based on the optimal control algorithm of adaptive dynamic programming (ADP). The state space model of the working face fluid supply system in the process of no-load column lifting of hydraulic support is first established using the flow relationship, and the effectiveness of the proposed control algorithm is then verified by simulation validation. Moreover, combined with a certain fluid supply system of a fully mechanized caving face in Shandong Energy Xinwen Group XinJulong Co., Ltd, a technical scheme of adaptive stable fluid supply is verified in engineering practice. The results indicate that the fluid supply system using the proposed control algorithm has a favorable tracking effect on the ideal trajectory, and the tracking error can converge to near zero. The output pressure of the fluid supply system using the stable fluid supply technology is more stable, and the practical effect is good, which meets the demand of stable fluid supply in the mining face.
