智能寻迹模型车的控制策略及算法研究

Study on control strategy and algorithm based on intelligent-searching track car model

在输入信号及硬件有限的条件下,运用一种有效寻迹、转向与速度控制算法,对于提高智能车的运动性能,有着重要的作用。为提高智能车的性能,对控制算法进行了研究。针对传统的路径离散识别算法只能获得少而离散化路径信息的问题,提出了采用连续化路径识别算法对路径信息采集;针对制约智能车快速寻迹的转向及速度问题,提出了采用优化的PID控制算法对智能车的舵机和电机进行控制。实验结果表明,与传统方法相比,采用连续的信号、基于反馈控制的PID控制算法,智能车的快速性、灵敏性、稳定性明显改善,从而验证了算法的可行性。

Under the conditions of limited hardware and input signal,an efficient track-searching,turning and speed control algorithm is of great clinical significance in improving the performance of intelligent vehicle.To improve the performance,the control algorithms were studied.Compared with the traditional path of discrete recognition algorithms that cannot get enough information of path conditions,which is discrete and not continuous,the continuous path recognition algorithm is applied to collect track information; against the problems that direction and speed constrain the intelligent vehicle＇s fast tracking,the optimized PID control algorithm is used to control the intelligent vehicle＇s steering engine and motor.The experimental results show that different from traditional methods,using continuous information and PID control algorithm based on feedback controls,its rapidity,sensitivity and stability are obviously improved,and thus the feasibility of these algorithms is verified.