摘要
为了克服传统循迹车控制算法中参数固定以及环境适应性不强的问题,提出了一种基于嵌入式CPU的自适应智能循迹车控制算法。该方法将参数列表引入到传统PID控制理论中,在车辆的运行过程中,CPU周期性的读取外围传感器数据并计算误差信息,同时根据车辆运行状态,遍历列表中的PID参数,选取环境适应性最好的一组作为当前控制参数。实验表明,该方法具有较强的环境适应性,同时大大降低了算法调试的工作量。
In order to overcome the problem of fixed parameters and weak environmental adaptability- in traditional tracking vehi- cle control algorithms, an adaptive intelligent tracking vehicle control algorithnl based on embedded CPU is proposed. The method in- troduces the parameter list into the traditional PID control theory. During the running of the vehicle, the CPU periodically reads out the peripheral sensor data and calculates the error information. At the same time, according to the running status of the vehicle, it traverses the PID parameters in the list and select the best environmental adaptability- group as the cmTent control parameters. Exper- iments show that this method has strong environmental adaptability- and greatly reduces the workload of algorithm debugging.
出处
《科技创新与应用》
2018年第22期19-21,共3页
Technology Innovation and Application
基金
江汉大学博士启动基金(编号:1008-06600001)
