基于免疫模糊PID算法的农机机器视觉研究

Research on Machine Vision of Agricultural Machinery Based on Immune Fuzzy PID Algorithms

为了提高农机视觉系统的精度及无人驾驶农机的导航效率,将免疫模糊PID算法引入到了收割机视觉控制系统的设计中,通过PID控制器反馈误差后,利用免疫算法和模糊控制算法对导航追踪误差进行修正,从而有效地提高了导航的精度。为了验证该方法的可行性,设计了基于免疫模糊PID算法的农机导航追踪误差修正系统,并分别对不使用PID算法、单独使用PID算法和综合使用免疫模糊PID算法的农机导航误差进行了测试,结果表明:综合使用免疫模糊PID算法的农机导航误差最小,从而验证了方法的可靠性。

In order to improve the precision of agricultural machinery vision system and the navigation efficiency of unmanned agricultural machinery, it introduced the immune fuzzy PID algorithm into the design of harvester vision control system. After feedback error of the PID controller, the navigation tracking error is corrected by the immune algorithm and the fuzzy control algorithm, thus effectively improving the navigation accuracy. In order to verify the feasibility of this method, it designed a tracking error correction system for agricultural machinery navigation based on immune-fuzzy-PID algorithm. It tested the navigation errors of agricultural machinery without using PID algorithm, using PID algorithm alone and using immune-fuzzy-PID algorithm in combination. The test results show that the navigation errors of agricultural machinery using immune-fuzzy-PID algorithm are the smallest, which verifies the method. The reliability of the method.