The paper presents a method of robot skateboard edging grinding based on pneumatic constant force device. To solve the problem of modeling and complex algorithm of robot end active compliance control during the grinding process, a hybrid position/force control is proposed by controlling position and force separately. That is, a kind of 2 degrees of freedom pneumatic constant force grinding device is designed to realize the constant force control in the horizontal and vertical directions, while a robot is used only for position control. Then a fuzzy PID control algorithm is proposed for smooth grinding based on the dynamic modeling of the grinding device. Experiments show that the use of fuzzy PID can effectively improve the dynamic adjustment performance of the pneumatic constant force grinding system and reduce the steady-state error. Compared with normal PID, fuzzy PID reduces the step response adjustment time of the grinding system from 400ms to within 200ms. In addition, when the constant force control is disturbed, the response adjustment time is less than 100ms and there is no oscillation, and the standard deviation of the grinding force is within 1N, which has good robustness and fulfills the requirements of edging control.
Rail defects appear in a greater variety and frequency with the rapid development of High-Speed Rail (HSR), which seriously affects the safe operation of trains. Rail grinding is one of the common methods used to eliminate these defects. However, the quality of rail grinding is often limited by the constant power control method. This paper presents a fuzzy adaptive PID control method based on PID control. In this method, a fuzzy rule library of input and output is established according to the experience of experts and grinding operators, and the PID control parameters can be adjusted in real time through the library to achieve the purpose of constant power grinding. Compared with classical PID, the effectiveness of the proposed method was verified by simulation and the rail grinding experiment with the designed equipment. Experimental results showed that the power data of fuzzy adaptive PID control had less fluctuation, which could be basically stabilized at 5KW±0.1KW, and the curve tracking error was reduced by 60.9%. It is concluded that this method can greatly improve the power accuracy and stability of rail grinding.INDEX TERMS HSR, rail grinding, constant grinding power, fuzzy adaptive PID, accuracy and stability.
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