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上传于：2013-11-20

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    188宝金博页面版: 神经网络PID在温度控制系统中的研究与仿真-中英文资料

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    内容提示： Exploration And Simulation of Neural Network PID In Temperature Control System Abstract ： This paper presents a new kind of intelligence PID control method on BP neural network and some of basic concepts about BP neural network . Neural network intelligence PID controller has many advanced properties compared with traditional PID controller. The BP neural network PID control method is applied to temperature control system in industry field. The simulation resu...

    文档格式：DOC | 页数：9 | 浏览次数：21 | 上传日期：2013-11-20 12:04:20 | 文档星级：
    Exploration And Simulation of Neural Network PID In Temperature Control System Abstract ： This paper presents a new kind of intelligence PID control method on BP neural network and some of basic concepts about BP neural network . Neural network intelligence PID controller has many advanced properties compared with traditional PID controller. The BP neural network PID control method is applied to temperature control system in industry field. The simulation results show that the control method has high control accuracy ,strong adaptation and excellent control results. Key words ： Neural network , PID controller , Temperature control system 1 Foreword In industrial process control, PID control is a basic control method, its robustness, simple structure, easy to implement, but the conventional PID control also has its own disadvantage, because the parameters of conventional PID controller is based on being mathematical model of controlled object identified, when the mathematical model of the object are changing, non-linear time, PID parameters is not easy in accordance with its actual situation and make adjustments, the impact of the quality control so that the control of the quality control system decline. Especially in the pure time-delay characteristics with the industrial process, the conventional PID control more difficult to meet the requirements of the control accuracy. Because of neural networks with self-organization, self-learning, adaptive capacity, In this paper, based on BP neural network PID controller, so that artificial neural network PID control with the traditional combination of each other and jointly improve quality control and to the method in the temperature control system using the simulation language Matlab application. 2 BP neural network model and algorithm constitute 2.1 BP neural network model constitute BP neural network learning process constituted mainly by two stages: The first phase (forward propagation), the input signal through the input layer, hidden layer after layer-by-layer treatment, in the output layer is calculated for each neuron the actual output value. The second stage (the process of error back-propagation), if not in the output layer the desired output value, the actual layer-by-layer recursive output and desired output of the margin, and the right to adjust the basis of this error factor. 2.2 The neural network PID controller structure and algorithm In the traditional PID control, classical incremental PID control forms:

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