Neural network speed controller for drive system with elastic joint

M. Kaminski
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引用次数: 4

Abstract

This paper presents application of neural network for speed control of drive system with elastic connection. Analyzed object is characteristic due to complexity of the mechanical part of the drive. Motor machine is connected with load using long elastic shaft. Such form of electromagnetic torque transmission leads to appearing of oscillation in state variables transients. In result precise control of the speed or position is difficult to obtain. In article application of neural network trained on-line is applied in speed control loop. Weights coefficients are recalculated according to backpropagation algorithm based on error from reference model placed in control structure. Several simulation tests are presented. Obtained results presents quality of control using described neural model. In addition robustness against parameter changes is shown. Moreover influence of introduction of nonlinear elements (backlash) on achieved results is analyzed. Simulations are verified experimentally on laboratory benchmark. Control algorithm is implemented in dSPACE 1104.
弹性关节驱动系统的神经网络速度控制器
本文介绍了神经网络在弹性连接传动系统速度控制中的应用。由于传动机械部分的复杂性,分析对象具有一定的特殊性。电机与负载采用长弹性轴连接。这种形式的电磁转矩传递导致状态变量瞬态出现振荡。因此,很难精确地控制速度或位置。本文将在线训练的神经网络应用于速度控制回路。根据控制结构中参考模型的误差,采用反向传播算法重新计算权系数。给出了几个仿真试验。得到的结果表明,采用描述的神经模型控制的质量。此外,还显示了对参数变化的鲁棒性。此外,还分析了非线性单元(间隙)的引入对所得结果的影响。仿真结果在实验室基准上得到了验证。控制算法在dSPACE 1104中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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