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基于BP神经网络的PID参数自整定的研究
是M文件，控制效果非常好-Based on BP Neural Network PID parameter self-tuning of the Study are M documents, control has very good results
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准对角递归小波神经网络PID算法，其控制效果要比常规的多变量PID控制算法要好的多-Design of multivariable self-tuning PID controllers via Quasi-Diagonal Recurrent wavelet Neural Network
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本文把神经网络技术应用在PID控制中，充分利用神经网络具有非线性函数逼近能力构造神经网络PID自整定控制器。-This paper, the neural network technology used in PID control, the full use of neural network structure with nonlinear function approximation capability PID self-tuning neural network controller.
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基于BP神经网络的PID控制，利用神经网络的自学习、非线性和不依赖模型等特性实现PID参数的在线自整定，充分利用PID和神经网络的优点。-BP neural network based PID control, self-learning neural network, nonlinear and non-dependent model and other characteristics to achieve PID parameters on-line self-tuning, full us
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模糊参数自整定PID控制模糊推理规则，本规则考虑到偏差很小时，提前使系统减速，基本无超调-Fuzzy parameter self-tuning PID control rules of fuzzy inference
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