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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
Tel:
86-571-87041360,87239525
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86-571-87239571
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No.9 Gaoguannong,Daxue Road,Hangzhou,China
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meem_contribute@163.com
Abstract: The piston cylinder system controlled by proportional valve has the problem of tedious manual tuning of PID parameters. In order to solve the problem of tuning the control parameters of the variable mechanism of the four-distribution axial piston motor, a parallel collaborative design method based on particle swarm optimization (PSO) was proposed. Firstly, the swashplate nclination of the four-port axial piston motor was controlled by PID closed-loop control composed of servo proportional valve and the angular displacement sensor fixedly connected with the swash plate, and changedthe output shaft speed of the four-port axial piston motor.Then the Simulation X was used to model the variable displacement fourport axial piston motor and the valve-controlled variable mechanism.Finally, a parallel collaborative design method based on particle swarm optimization algorithm was proposed to solve the control parameter tuning problem of variable mechanism of four-port axial piston motor without hydraulic simulation software platform, which could be used for automatic optimization and tuning of PID parameters to reduce control tracking error. The results show that compared with the system without optimizing the control parameters, after optimizing the control parameters, the overshoot of the swing angle of the motor swashplate is reduced by 21%, the peak pressure in the plunger cavity is reduced by 3.4MPa, and the motor speed is stable, which provides a theoretical basis for the subsequent construction of the physical prototype of the variable displacement four-port axial piston motor.
Key words: axial piston motor; hydraulic system; particle swarm optimization(PSO); multi-thread parallel cooperation; control parameter tuning; proportional valve; swashplate inclination