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  • Công bố khoa học và công nghệ Việt Nam

28.19

Khoa học máy tính và thông tin

Ngô Văn Thuyên, Đoàn Xuân Nam, Mai Nhật Thiên, Huỳnh Thanh Loan(1)

Điều khiển giảm dao động cần trục không dùng cảm biến góc sử dụng mạng nở ron

Sensorless control for swing reduction of overhead crane by using neural network

Khoa học và Công nghệ các trường đại học kỹ thuật

2014

102

17-21

0868-3980

Sensorless control in a physical system helps reduce the equipment cost and increase the working liablility. In this paper, a control algorithm to reduce the swing angle of the load of an overhead crane without using sensors for angle measurement to reduce the cost as well as increase the reliability of the system was presented. The load position was controlled by a PID controller. An anti-swing controller for the crane was designed using a feed forward neural network with one: hidden layer and the backpropagation learning rule. A PID current controller was also designed to limit the current of the motor driving the load. The simulation result on MatLab as well as the experiment data on a real overhead crane system model controlled by DSP TMS320F28335 of Texas Instrument showed that the swing angle of the load was reduced significantly and comparable with that of sytems using angle sensor.

TTKHCNQG, CTv 140