KEYWORDS: Control systems, Sensors, Computing systems, Data modeling, Signal detection, Fuzzy logic, Detection and tracking algorithms, Wavelets, Signal processing, Computer intrusion detection
For special systems such as nonlinear large time delay, there is a problem that the control effect of conventional PID controller is not ideal. Therefore, a fuzzy-PID control method is proposed by combining the advantages of fuzzy control and conventional PID control. By combining different basic features, this method makes the meaning of alarm clearer, and has better scalability and success. At the same time, it provides a good platform for information interaction of anomaly detection. The electronic devices in the computer control system mostly work in high-voltage environment. The working intensity of the sensor is very high, but its high precision determines that its fault characteristic pole signal is easily interfered. In the hydraulic control system, the technical state of the sensor in the detection link directly affects the working performance of the system. Fuzzy controller can control complex and unclear systems simply and effectively. Therefore, combining the advantages of traditional PID and controller, and considering the characteristics of fuzzy control, the idea of fuzzy PID and controller is put forward. The simulation experiment on the actual power load data proves that this method can accurately detect the abnormal data online and provide correct abnormal data correction.
Thickness accuracy is one of the important quality indexes of strip products. With the development of social economy, the quality requirements of strip products are higher and higher, and the requirements for precision are also higher and higher. Many original production lines have been unable to meet the requirements, the existing unqualified production line transformation becomes very urgent. A control scheme of thickness control system of cold rolling mill based on Siemens S7-400PLC is presented. How to improve in a stable in the process of rolling steel strip thickness control precision, and improve the yield of plate and strip, is today a most popular courses in the field of the strip thickness control, aluminum plate is in hot rolling process of cold rolling mill or coil as wool roll casting process, a multiple passes, the rolling rolling out the qualified finished product coil, A rolling mill that provides billets for sheet shearing, stretching and bending straightening and aluminum foil deep processing. Artificial neural network technology has been successfully applied in many fields of automation system, such as system modeling and identification, robot control, system pattern discrimination, system fault diagnosis and so on. In the lag link of AGC system, the self-learning ability of the neural network is used to adjust the integral controller parameter value online. The weight of the neural network is corresponding to the integral parameter value, and the integral parameter can be adjusted according to the dynamic characteristics of the controlled system, thus improving the adaptive ability of the regulator.
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