Aiming at the chaos control of permanent magnet synchronous motor, a dual-parameter collaborative intelligent optimal control method based on GWO-RBFNN was proposed. Starting from the perspective that the controller can automatically search for the expected motion state, the distance between two points on the Poincaré cross section is selected as the controller input. And considering the coupling effect of system parameters on the dynamic behavior of the system, a dualparameter cooperative controller is designed based on radial basis function neural network (RBFNN); Grey Wolf Optimization (GWO) algorithm is used to optimize the selection of controller parameters; By slightly adjusting the two controllable parameters of the system, the chaotic motion of the PMSM system is controlled to the expected motion state. In the simulation study, compared with the single-parameter intelligent optimization control method based on GWO-RBFNN, the results show that although both methods can achieve chaotic motion control, the control speed of the dual-parameter collaborative intelligent optimization control method based on GWO-RBFNN is faster and overshoot is smaller.
KEYWORDS: Sensors, Sensor networks, Design and modelling, Safety, Network landslides, Data processing, Data communications, Telecommunications, Soil moisture, Education and training
foreign matter intrusion on train operation safety is becoming increasingly serious. Based on a large amount of research data, among many factors affecting the operation safety of high-speed railway, the detection of personnel and foreign matter intrusion is difficult, and the preventive measures are limited, mainly because of its strong randomness and complexity. This paper systematically introduces the development status of high-speed railway line protection technology at home and abroad, especially summarizes the development status of high-speed railway line monitoring technology in China, and proposes a new design of foreign object intrusion detection and alarm device based on new sensors and networks, which has certain reference value for high-speed railway line protection and railway bureaus and departments in related fields.
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