The Development Of Neural Network Control System For Nonoperative Treatment Equipment Spinal Decompression

Control system is the key subsystems of nonoperative treatment of spinal reduced pressure equipment. According to reduce pressure feedback perception patients muscle contraction resistance, it can adjust treatment parameters, make the vertebral muscles in the flabby condition, Prevent muscle being stretched excessive, Keep reducing pressure and consistent treatment curve. Because of equipment’s loading characteristics and the environment where the equipment is used, the traditional PID control methods are hard to meet the control precision requirements. Because its adaptability, the neural network control method get very big development in recent years. In this paper, neural network control method which is used in nonoperative spinal reduced pressure equipment has been studied, the main work is the following:1This paper introduces the development history of neural network control, expounds the neural network and e development of its control technology at home and abroad;2The neural network control model is identified. Both at home and abroad, the researchers suggest a variety of neural network control models, several kinds of control models are contrasted to confirm the system used in the neural network control model;3The determination of control model main parameters and excitation function. Through a lot of experiments comparative study, ensure the network excitation function, learning step length, integral step length, system control frequency and system constant parameters.4Development of control software. Based on the front of the control method, ensure the development of the equipment control software.