Fuzzy control and co-simulation for semi-active suspension based on improved genetic algorithm

Author(s):  
Jingjun Zhang ◽  
Zhiqiang Xu ◽  
Ruizhen Gao
Author(s):  
Xiaojia Pang ◽  
Yuwen Ning

The advancement of science has made computer technology and the education industry more and more closely related, and the development of intelligent teaching systems has also opened a new path for classroom teaching. This paper studies the application of fuzzy control based on genetic algorithms in the intelligent psychology teaching system. Facing the complicated variables in the teaching process, the improved genetic algorithm can better realize dynamic teaching decisions through fuzzy control. This article aims to improve the quality of psychology classroom teaching, and develops an intelligent psychology teaching system based on the fuzzy control theory of genetic algorithm. Combined with the current development of fuzzy control theory, the problems existing in the intelligent teaching system are studied and analyzed, and they have been optimized and improved. This paper proposes a control algorithm based on a teaching management system. The algorithm can implement fuzzy control on student models, knowledge organization structure, intelligent test papers and teaching decision-making. While restoring the real teaching process, it can better realize teaching students in accordance with their aptitude and improve teaching. The intelligence of the system. According to the system test data, the proportions of the difficulty of the system’s automatic test paper are 30.1%, 51.6%, 18.3%, which are in line with the designer’s set expectation of 3 : 5:2, which shows the improved genetic algorithm. It can realize the intelligent volume group function very well.


2010 ◽  
Vol 143-144 ◽  
pp. 929-932
Author(s):  
Jing Jun Zhang ◽  
Zhi Qiang Xu

Establishing a 2-DOFs of 1/4 semi-active suspension system model, using genetic algorithm approach, to design fuzzy logic controller of the semi-active suspension and simulate in the environment of Matlab/Simulink. The results of being compared with the passive suspension demonstrate is that this developed fuzzy logic controller based on genetic algorithm enhances the performance of the full car suspension system significantly.


2010 ◽  
Vol 44-47 ◽  
pp. 1492-1495 ◽  
Author(s):  
Rui Zhen Gao ◽  
Zhi Qiang Xu ◽  
Jing Jun Zhang

This paper establish a multi-body dynamic model of the Vehicle. The fuzzy logic controller was designed for the semi-active suspension based on improved genetic algorithm, then, the co-simulation were carried out based on Adams and Matlab/Simulink. The results demonstrate that this control method enhances the performance of the full car suspension system significantly.


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