负载波动条件下阀控液压马达转速的精确控制算法。

IF 2.6 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Science Progress Pub Date : 2024-10-01 DOI:10.1177/00368504241296299
Kai Hu, Wenyi Zhang
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引用次数: 0

摘要

本研究重点分析和设计了一种新型模糊自适应 PID 控制算法,旨在提高阀控液压马达在负载波动条件下的速度控制精度。根据既定的液压技术方案,采用模型识别方法计算阀控液压马达的传递函数。随后对阀控液压马达的底盘进行了研究,并利用谐波叠加法构建了 E 级路面的模型。通过动态仿真,确定了两种常见工作条件下的负载波动范围。随后详细设计了模糊自适应 PID 算法,将误差及其变化率作为输入参数,将比例系数、积分常数和微分常数的增量作为输出参数。联合仿真数据表明,与 PID 算法相比,模糊自适应 PID 算法的平均误差可减少 50%以上,上升时间缩短了 0.04 秒。为验证理论分析,开发并测试了履带式液压底盘。在 200 转/分钟的预期速度下,平均误差减少了 1.68 转/分钟;在 1000 转/分钟的预期速度下,平均误差减少了 2.68 转/分钟。所设计的智能控制算法可有效提高负载波动条件下的控制精度和稳定性。
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Precise control algorithm of rotational speed of the valve-controlled hydraulic motor under load fluctuating conditions.

The present study focuses on the analysis and design of a novel fuzzy adaptive PID control algorithm, aiming to enhance the speed control accuracy of valve-controlled hydraulic motors under load fluctuating conditions. The method of model identification was adopted to calculate the transfer function of valve-controlled hydraulic motor based on the established hydraulic technology scheme. The chassis of the valve-controlled hydraulic motor is subsequently investigated, and a model for E-grade pavement is constructed using the harmonic superposition method. Through dynamic simulation, the load fluctuation range under two common operating conditions is determined. The fuzzy adaptive PID algorithm was subsequently designed in detail, with the error and its rate of change being considered as input parameters, while the increments of the proportional coefficient, integral constant, and differential constant were regarded as output parameters. Co-simulation data indicate that, compared with the PID algorithm, the average error of the fuzzy adaptive PID algorithm can be reduced by more than 50% and the rise time is reduced by 0.04 seconds. To validate the theoretical analysis, a tracked hydraulic chassis was developed and tested. At an expected speed of 200 rev/min, the average error decreased by 1.68 rev/min, while at an expected speed of 1000 rev/min, the average error reduced by 2.68 rev/min. The designed intelligent control algorithm can effectively improve the control accuracy and stability under load fluctuating conditions.

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来源期刊
Science Progress
Science Progress Multidisciplinary-Multidisciplinary
CiteScore
3.80
自引率
0.00%
发文量
119
期刊介绍: Science Progress has for over 100 years been a highly regarded review publication in science, technology and medicine. Its objective is to excite the readers'' interest in areas with which they may not be fully familiar but which could facilitate their interest, or even activity, in a cognate field.
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