智能小车路径识别的模糊控制模式研究  

Research on Fuzzy Controlling Model for Smart Car's Track Recognition

作　　者：陈卫[1] 陈平[2] 赵鹏举[2] 李毅[2] 

机构地区：[1]重庆电子工程职业学院电子信息系,重庆401331 [2]重庆电子工程职业学院计算机系,重庆401331

出　　处：《微计算机信息》2011年第10期20-22,共3页Control & Automation

摘　　要：在嵌入式智能小车系统中,针对特定的运行环境,设计采用了线阵式红外光电探测器;通过行进过程分析,确定了各种状态模型和处理规则;运用模糊模式识别技术,建立了差速偏转模糊控制数学模型,有效解决了小车自动路径识别、障碍识别和标志区域识别问题,以及行驶偏转控制问题;通过指定空白区域直线行驶规则解决了不连续段的处理问题,规定暂停区的启动直线行驶0.2～0.5S消除了重复启停问题,采用多峰波形简化归并为单峰模型消除了多峰波形模糊控制模型中的多义性问题。实测证明了该模糊控制模型的正确性。In embedded smart car system,the linear array infrared sensors are designed for special track.All kinds of running models and processing methods are worked out by analyzing special track and driving states.Using fuzzy controlling technology,the mathematics model of fuzzy controlling with difference speed deflection is founded,and a lot of problems of automatic track recognition,obstacles recognition,symbol area recognition and running deflection are solved.The beeline driving rule is defined to deal with the discontinuity track in obstacles empty area.The repeat starting-stopping problem is solved by beeline driving for 0.2 to 0.5 second in symbol area.In order to avoid the multivocal problem by fuzzy controlling,the two three rectangles wave model is predigested to single rectangle wave model.The correctness of the proposed fuzzy controlling model is proved through smart car running tests in special track.

关 键 词：模糊控制 嵌入式系统 智能小车 路径识别 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]