Paper
1 August 2022 Longitudinal motion control of autonomous vehicle based on feedforward-fuzzy PI
Xin Jiang, Haitao Xing, Shenghua Chen
Author Affiliations +
Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 1225742 (2022) https://doi.org/10.1117/12.2640337
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China
Abstract
Longitudinal motion control of unmanned vehicles refers to the accurate speed control by driving or braking system. Due to the nonlinearity and parameter uncertainties of the vehicle system and the desired speed changing in various driving environment, the longitudinal motion control of unmanned vehicles is difficult to realize. To solve the problem, a longitudinal motion controller of autonomous vehicle based on feedforward-fuzzy PI is designed in this paper, which is divided into upper controller and lower controller according to the control flow. The upper controller is the proposed feedforward-fuzzy PI controller, including a feedforward controller and a fuzzy PI controller. The lower controller includes a logic switching controller and an inverse longitudinal vehicle model. In order to verify the effectiveness of the proposed controller, Simulink and CarSim are used to build a co-simulation platform. The simulation results show that when the autonomous vehicle desired speed changes, the control accuracy of the proposed controller is higher than that of the traditional controller, and thus the longitudinal motion control of the vehicle can be better realized.
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Xin Jiang, Haitao Xing, and Shenghua Chen "Longitudinal motion control of autonomous vehicle based on feedforward-fuzzy PI", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 1225742 (1 August 2022); https://doi.org/10.1117/12.2640337
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KEYWORDS
Motion controllers

Unmanned vehicles

Vehicle control

Control systems

Device simulation

Fuzzy logic

Control systems design

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