Design of tracking car based on fuzzy PID control
Pages 219 - 223
Abstract
Taking the IAP15F2K61S2 MCU as the core of the controller, a fuzzy PID control algorithm is used to design a car which can easily realize the intelligent tracking and obstacle avoidance function. At first, the infrared photoelectric sensor of the car detects the road information and obstacles, and then the offset angle and the offset change rate are transmitted as two input quantities to the fuzzy PID controller. After processing, the corresponding signals are output to control the speed and direction of the car movement. In this way, it shortens the system execution time and improves the system response speed. Experiments show that the fuzzy PID control strategy has obvious advantages in the tracking accuracy and speed of smart cars.
References
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Han Linfeng, Cui Qi. Automatic tracking car position and speed control {J}. electronic production, 2018 (15): 45--48.
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Liu Xiaojun, Yuan Zhongbing (2017). Design of Smart Car Control System Based on Camera. Acta Electronica Malaysia, 1(1): 15--17.
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Yu Sally, Liu Xiaolong, Zhou Jianmin. Speed control of intelligent car based on fuzzy PID and algorithm {J}. Automation and instrumentation, 2016 (02): 76--77.
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Yang Hui, Gao Xiang. Autonomous Tracking Vehicle Control Based on Fuzzy PID {J}. Industrial Instruments and Automation Devices, 2017 (04): 92--96+100.
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Index Terms
- Design of tracking car based on fuzzy PID control
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Published In
December 2018
365 pages
ISBN:9781450365703
DOI:10.1145/3305275
Copyright © 2018 ACM.
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- International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 29 December 2018
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- Short-paper
- Research
- Refereed limited
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ISBDAI '18
ISBDAI '18: International Symposium on Big Data and Artificial Intelligence
December 29 - 30, 2018
Hong Kong, Hong Kong
Acceptance Rates
ISBDAI '18 Paper Acceptance Rate 70 of 340 submissions, 21%;
Overall Acceptance Rate 70 of 340 submissions, 21%
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