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1、英文原文：Realization of Neural Network Inverse System with PLC in Variable Frequency Speed-Regulating System Abstract. The variable frequency speed-regulating system which consists of an induction motor and a general inverter, and controlled by PLC is widely used in industrial field. .However, for the m
2、ultivariable, nonlinear and strongly coupled induction motor, the control performance is not good enough to meet the needs of speed-regulating. The mathematic model of the variable frequency speed-regulating system in vector control mode is presented and its reversibility has been proved. By constru
3、cting a neural network inverse system and combining it with the variable frequency speed-regulating system, a pseudo-linear system is completed, and then a linear close-loop is designed to get high performance. Using PLC, a neural network inverse system can be realized in system. The results of expe
4、riments have shown that the performances of variable frequency speed-regulating system can be improved greatly and the practicability of neural network inverse control was testified.1.Introduction In recent years, with power electronic technology, microelectronic technology and modern control theory
5、 infiltrating into AC electric driving system, inverters have been widely used in speed-regulating of AC motor. The variable frequency speed-regulating system which consists of an induction motor and a general inverter is used to take the place of DC speed-regulating system. Because of terrible envi
6、ronment and severe disturbance in industrial field, the choice of controller is an important problem. In reference 123, Neural network inverse control was realized by using industrial control computer and several data acquisition cards. The advantages of industrial control computer are high computat
7、ion speed, great memory capacity and good compatibility with other software etc. But industrial control computer also has some disadvantages in industrial application such as instability and fallibility and worse communication ability. PLC control system is special designed for industrial environmen
8、t application, and its stability and reliability are good. PLC control system can be easily integrated into field bus control system with the high ability of communication configuration, so it is wildly used in recent years, and deeply welcomed. Since the system composed of normal inverter and induc
9、tion motor is a complicated nonlinear system, traditional PID control strategy could not meet the requirement for further control. Therefore, how to enhance control performance of this system is very urgent.The neural network inverse system 45 is a novel control method in recent years. The basic ide
10、a is that: for a given system, an inverse system of the original system is created by a dynamic neural network, and the combination system of inverse and object is transformed into a kind of decoupling standardized system with linear relationship. Subsequently, a linear close-loop regulator can be d
11、esigned to achieve high control performance. The advantage of this method is easily to be realized in engineering. The linearization and decoupling control of normal system can realize using this method.Combining the neural network inverse into PLC can easily make up the insufficiency of solving the
12、 problems of nonlinear and coupling in PLC control system. This combination can promote the application of neural network inverse into practice to achieve its full economic .In this paper, firstly the neural network inverse system method is introduced, and mathematic model of the variable frequency
13、speed-regulating system in vector control mode is presented. Then a reversible analysis of the system is performed, and the methods and steps are given in constructing NN-inverse system with PLC control system. Finally, the method is verified in traditional PI control and NN-inverse control.2.Neural
14、 Network Inverse System Control MethodThe basic idea of inverse control method 6 is that: for a given system, an-th integral inverse system of the original system is created by feedback method, and combining the inverse system with original system, a kind of decoupling standardized system with linea
15、r relationship is obtained, which is named as a pseudo linear system as shown in Fig.1. Subsequently, a linear close-loop regulator will be designed to achieve high control performance.Inverse system control method with the features of direct, simple and easy to understand does not like differential
16、 geometry method 7, which is discusses the problems in geometry domain. The main problem is the acquisition of the inverse model in the applications. Since non-linear system is a complex system, and desired strict inverse is very difficult toobtain, even impossible. The engineering application of inverse system control dont meet the expectations. As neural network has non-linear approximate ability, especially for nonlinear the powerful tool
