基于改进粒子群优化模糊控制的农业车辆导航系统  

Navigation System of Agricultural Vehicle Based on Fuzzy Logic Controller with Improved Particle Swarm Optimization Algorithm

作　　者：孟庆宽[1] 仇瑞承 张漫[1] 刘刚[1] 张志刚[2] 项明 

机构地区：[1]中国农业大学现代精细农业系统集成研究教育部重点实验室,北京100083 [2]华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州510642 [3]农业部农业信息获取技术重点实验室,北京100083

出　　处：《农业机械学报》2015年第3期29-36,58,共9页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家高技术研究发展计划(863计划)资助项目(2012AA101901);引进国际先进农业科学技术计划(948计划)资助项目(2011-G32)

摘　　要：以采用机器视觉导航的农业车辆为研究对象,提出了一种基于改进粒子群优化自适应模糊控制的农机导航控制方法。建立了车辆2自由度转向模型和视觉预瞄模型,对车辆横向控制进行状态描述。对粒子群算法进行了改进,提高了粒子群算法的收敛速度,降低了算法计算时间。构建了自适应模糊控制器,在模糊控制器中引入加权因子,以横向偏差和航向偏差时间误差绝对值积分(ITAE)之和作为系统目标函数,通过粒子群算法计算得到最优加权因子,进而调整控制规则实现导航车辆的自适应控制。仿真和导航试验结果表明,提出的控制方法可以迅速消除横向误差,具有超调量小、响应速度快等特点,既保留了模糊控制算法的优点,又提高了系统控制品质。在相同参数条件下,与常规模糊控制相比,改进模糊控制算法导航精度显著提高。当车速为0.8/s时,直线路径跟踪最大横向偏差不超过4.2 cm,曲线路径跟踪最大横向偏差不超过5.9 cm,能够较好地满足农业车辆导航作业要求。Taking agricultural vehicle with machine vision navigation as study object, a self-adaptive fuzzy control method with improved particle swarm optimization algorithm was designed. Firstly, by establishing 2-DOF steering model and visual preview model, lateral control equations of vehicle were described. Secondly, in order to improve the convergent speed of particle swarm optimization （PSO） algorithm,an improved PSO algorithm was designed. Finally, agricultural vehicle guidance system was a complex system with high nonlinearity, time-varying and large delay; therefore, an adaptive fuzzy controller was used for path tracking control. Correction factors were introduced into the fuzzy controller and particle swarm algorithm was used to optimize the correction factors. Taking the integral time absolute error （ITAE） sum of lateral offset and heading offset as the objective function, optimal correction factors were calculated by using PSO algorithm. Simulation and experimental results showed that the designedcontrol algorithm could eliminate the lateral offset rapidly with less overshoot and rapid response. It retained the advantages of fuzzy control method and improved the control quality of guidance system. Compared with standard fuzzy control method, the improved fuzzy control method has a significant improvement on navigation accuracy under the same parameters condition. When the velocity of vehicle was O. 8 m/s, the maximum lateral offset of straight path and curve path were less than 4.2 cm and 5.9 cm respectively, which could meet the requirement of agricultural vehicle navigation.

关 键 词：农业车辆 导航 路径跟踪 自适应模糊控制 粒子群算法 

分 类 号：TP242.62[自动化与计算机技术—检测技术与自动化装置] TP391.41[自动化与计算机技术—控制科学与工程]