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PID神经网络控制在全自动多叶光栅中的应用

Application of PID Neural Network to Dynamic Multi-leaf Collimator
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摘要 为满足全自动多叶光栅在Sliding工作模式下对光栅叶片的控制,要求具有很快的加速度和良好的动态性能以及很高的位置控制精度,提出了一种适用于该模式下的速度—位置双闭环电机控制模型,采用了神经网络与数字PID相融合的控制算法,并对该控制模型进行了仿真验证。实验表明:采用PID神经网络的速度—位置双闭控制具有很高的控制精度和良好的动态性能,能有效满足全自动多叶光栅Sliding工作模式的控制要求。 In order to meet the demand of the Dynamic Multi-leaf Collimator, that collimator should have high acceleration, good dynamic performance and high accuracy of position control at Sliding working mode, a speed-position double closed-loop cybernation model is put forward. Neural network combined with digital PID is used. This model is simulated and verified. The results indicate that neural network PID can provide high acceleration, good dynamic performance, which have already meet the requirement of Dynamic Multi-leaf Collimator at Sliding mode.
作者 沈昕 徐建南 戴志坚
机构地区 电子科技大学自动化工程学院
出处 《世界科技研究与发展》 CSCD 2010年第6期766-768,778,共4页 World Sci-Tech R&D
关键词 全自动多叶光栅 双闭环控制 PID神经网络 dynamic multi-leaf collimator speed-position double closed-loop control PID neural network
分类号 TP183 [自动化与计算机技术—控制理论与控制工程] TP273 [自动化与计算机技术—检测技术与自动化装置]
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参考文献8

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世界科技研究与发展
2010年 第6期

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