Solenoid valve type vibration damper control method based on non-linear neural fuzzy logic controller

Abstract

The invention discloses a solenoid valve type vibration damper control method based on a non-linear neural fuzzy logic controller. The method includes the steps of deeply optimizing input fuzzy variables, namely vertical vibration acceleration and vertical vibration speed of a vibration damping platform, and output fuzzy variables, namely membership function of a damping force coefficient, through a non-linear neural network method in smart control theory, and finally conducting real-time control on the solenoid valve type vibration damper through a control core. The solenoid valve type vibration damper control method solves the complex non-linear characteristic problem of a solenoid valve type vibration damper, and ensures riding comfortableness and operation stability. The vibration damping effect and the driving performance of a motor vehicle can be improved, and the service lifetime of the motor vehicle can be prolonged. The solenoid valve type vibration damper control method can be conveniently applied on semi-active suspension systems of various motor vehicles.

Description

technical field [0001] The application belongs to the field of control of automobile semi-active suspension systems, and relates to a vehicle vibration reduction technology, in particular to a control method of a solenoid valve type shock absorber based on a nonlinear neurofuzzy controller. Background technique [0002] At present, the suspension system of automobiles is mainly divided into passive suspension system and semi-active suspension system. Among them, because the suspension stiffness and damping force of the passive suspension system cannot be automatically adjusted with changes in vehicle speed, road conditions and other driving conditions, it is difficult to improve its ride comfort and road friendliness. The stiffness and damping force of the suspension elastic elements of the semi-active suspension system can be automatically adjusted according to the needs, so it can better meet the requirements of driving. Solenoid valve shock absorber is a kind of damper t...

AI Technical Summary

Problems solved by technology

Neural network control has the advantages of parallel computing, distributed information storage, good fault tolerance, and strong self-learning ability. However, it is not good at expressing fuzzy and structural languages. A random initial weight value, which leads to a greatly prolonged network learning time, which can easily cause the network learning to fall into a local extremum

Electromagnetic valve type shock absorber mainly has complex hysteresis and nonlinear characteristics. Because it is difficult to establish an accurate mathematical model, it is difficult to achieve a good control effect by conventional control.

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