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Optimal Learning Slip Ratio Control for Tractor-semitrailer Braking in a Turn based on Fuzzy Logic

Jinsong Donga, Hongwei Zhanga, Ronghui Zhangb,*, Xiaohong Jinc, Fang Chend

a Key Laboratory of Operation Safety Technology on Transport Vehicles, Research Institute of Highway Ministry of Transport, Beijing 100088, China.
b Xinjiang Laboratory of Perception & Control Technology for IOT, Xinjiang Nor-West Star Information Technology Co., Ltd, Urumqi 830011, China.
c Department of Transportation, School of Mines, China University of Mining and Technology, Xuzhou 221000, China.
d Xinjiang Communications Construction Group Co., Ltd, Urumqi 830016, China.

* Corresponding Author: Ronghui Zhang, email

Intelligent Automation & Soft Computing 2018, 24(3), 563-570.


The research on braking performance a of tractor-semitrailer is a hard and difficult point in the field of vehicle reliability and safety technology. In this paper, the tire braking model and the dynamic characteristic model of the brake torque with the variable of the controlling air pressure were established. We also established a nonlinear kinematic model of the tractor-semitrailer when it brakes on a curve. The parameters and variables of the model were measured and determined by the road experiment test. The optimal control strategy for the tractor-semitrailer based on the optimal slipping ratio was proposed. Then the PID controller and the fuzzy controller were designed respectively. Simulation results show that the reasonable control strategy can significantly improve the braking directional stability when a tractor-semitrailer runs on a curving road. The research results provide technical references for improving the lateral stability when a tractor-semitrailer brakes on a curve, and it also provides a technical reference for the road traffic safety.


Cite This Article

J. Dong, H. Zhang, R. Zhang, X. Jin and F. Chen, "Optimal learning slip ratio control for tractor-semitrailer braking in a turn based on fuzzy logic," Intelligent Automation & Soft Computing, vol. 24, no.3, pp. 563–570, 2018.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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