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基于神经网络算法电动助力自行车控制器设计
资料介绍
针对电动助力自行车动力辅助系统调速控制精度低、反应迟钝等问题,建立了分析电动助力自行车动力学模型,基于神经网络算法,设计了一种基于STM单片机的电动助力车控制器,该控制方法经神经网络回归后的隶度函数由模糊控制实时调整PID三个参数,对电动助力自行车速度进行实时控制。通过骑行测试,其结果显示,该控制器控制下的电机输出对脚踏速度有很强的跟随特性,且控制器具有实时性、高精度、高稳定性等优点,提高了在复杂环境的速度控制能力。
Aiming at the problems of low precision and slow response of the power assisted bicycle power assisted system, an analysis of the dynamic model of the electric assisted bicycle was established. Based on the neural network algorithm, an electric bicycle controller based on STM single chip was designed. After the neural network regression, the ordinate function is adjusted by the fuzzy control to adjust the PID parameters in real time, and the speed of the electric assist bicycle is controlled in real time. Through the riding test, the results show that the motor output under the control of the controller has strong follow-up characteristics for the pedaling speed, and the controller has the advantages of real-time, high precision, high stability, etc., and improves the complex environment. Speed control capability.
部分文件列表
| 文件名 | 大小 |
| 基于神经网络算法电动助力自行车控制器设计.pdf | 1M |
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