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Study on Deviation Control of Loader Working Device System

机译：装载机工作装置系统的偏差控制研究

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In order to fulfill the fixed-height lifting function of the loader working device and reduce the deviation between the memory value of the controller and the actual value, this paper starts with the experimental curve, identifies the root cause of the deviation firstly, then separately analyses the influence of load, speed and target value on the deviation through the experimental data, eliminates the unnecessary factor load on the basis of the control accuracy, and then studies the influence of speed and target value on the deviation, and predicts the deviation by curve fitting and neural network based on the existing data. Finally, the prediction deviation is verified by experiments. The validation results of fixed speed show that the prediction results of neural network deviation meet the accuracy requirement of 94.29% and the prediction results of curve fitting deviation meet the accuracy requirement of 85.71%. These two methods of deviation prediction can basically control the deviation in the range of ±1°. And a further optimization method of threshold control is proposed. The validation results of variable speed show that the method of controlling deviation in advance is still applicable to variable speed. And according to the experimental data of variable speed, an optimization method of reducing speed deviation control is proposed.
机译：为了满足装载机工作装置的固定高度提升功能并降低控制器的存储器值与实际值之间的偏差，本文从实验曲线开始，首先识别偏差的根本原因，然后单独地识别偏差的根本原因通过实验数据分析负载，速度和目标值对偏差的影响，无需基于控制精度的不必要的因子负载，然后研究速度和目标值对偏差的影响，并预测偏差基于现有数据的曲线拟合和神经网络。最后，通过实验验证预测偏差。固定速度的验证结果表明，神经网络偏差的预测结果符合94.29％的精度要求，曲线拟合偏差的预测结果符合85.71％的精度要求。这两种偏差预测方法基本上可以控制±1°范围内的偏差。提出了一种阈值控制的进一步优化方法。变速的验证结果表明，预先控制偏差的方法仍适用于可变速度。并根据变速的实验数据，提出了一种减少速度偏差控制的优化方法。

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