Abstract
In order to adjust shearer drum swiftly and precisely to adapt to the changes of coal seam, a compound control approach based on cerebellar model articulation control and fractional order PID controller was proposed. As the movement precision and response speed of hydraulic system were determined mainly by the control precision of valve-controlled asymmetrical hydraulic cylinder, its working principle and characteristics were analyzed in this paper, with particular focusing on the asymmetry problem. Furthermore, RBF neural network was applied to obtaining reasonable tuning parameters and a control algorithm of proposed controller was designed. Finally, laboratory experiments were developed to verify the validity and effectiveness of proposed compound control method. The testing results, compared with those for other controllers, proved that the proposed compound control method can acquire high movement precision and respond speed in the system of hydraulically driven shearer drum lifting with different control conditions.
Highlights
With the development of coal mining technology and stringent requirement for colliery safety, the automation control of fully mechanized coal face has become an inexorable trend
It is noteworthy that hydraulically driven shearer drum lifting has become one of the key technologies to improve the performance of hydraulic system [6]
In order to solve the control problems of hydraulically driven shearer drum lifting, this paper proposed a new compound control method based on Cerebellar model articulation control (CMAC) and fractional order PID (CMAC-PIλDμ) controller to control the hydraulic system
Summary
In order to adjust shearer drum swiftly and precisely to adapt to the changes of coal seam, a compound control approach based on cerebellar model articulation control and fractional order PID controller was proposed. As the movement precision and response speed of hydraulic system were determined mainly by the control precision of valve-controlled asymmetrical hydraulic cylinder, its working principle and characteristics were analyzed in this paper, with particular focusing on the asymmetry problem. RBF neural network was applied to obtaining reasonable tuning parameters and a control algorithm of proposed controller was designed. Laboratory experiments were developed to verify the validity and effectiveness of proposed compound control method. The testing results, compared with those for other controllers, proved that the proposed compound control method can acquire high movement precision and respond speed in the system of hydraulically driven shearer drum lifting with different control conditions
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