基于图像传感器的智能车控制系统开发
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摘要
智能汽车作为众多高新技术的综合载体,在智能交通系统中的扮演着重要的角色。本文以全国大学生智能汽车竞赛为背景,对智能车控制系统进行研究和设计。采用Freescale16位微处理器作为核心控制芯片,基于数字图像传感器采集视频图像,通过对采集的图像进行处理分析,获取道路信息,自主识别行驶路线,并结合测速反馈实现对车体的闭环控制,使智能车能够在规定的跑道上安全、快速地行驶。
论文的主要工作如下：
首先,针对控制要求对智能车系统的机械结构进行改造。结合现代汽车的相关理论,通过实验的方式对智能车底盘、前轮定位参数、齿轮传动机构、后轮及差速器进行了调整；讨论了图像传感器的安装原则与位置校正；分析了转向舵机对智能车系统产生的影响,为图像传感器与转向舵机设计出了合理、可靠的安装方式。
其次,文章对智能车系统的硬件电路进行了设计。分别对核心控制模块、电源管理模块、图像采集模块、电机驱动模块、舵机驱动模块、测速功能模块等部分的电路进行设计,保证智能车具有良好、稳定的硬件支撑。
最后,在智能车系统的软件设计中,给出了系统软件的总体架构,介绍了图像采集的流程,针对道路的特征给出了图像处理及路径识别的算法,从建模的角度对智能汽车的控制策略进行了分析和研究,在此基础上,借鉴生物免疫反馈机理并结合模糊理论,提出了一种模糊免疫自适应PID控制器,使智能车在高速行驶状态下的具有良好的目标轨迹跟踪性能。
As a carrier of many high-tech integrated, smart car plays an important role in intelligent transportation system. The smart car system uses the Freescalel6 bit microprocessor as a core control chip. The micro-controller obtains lane image information based on a digital image sensor then adjusts the model car's moving position and direction. The system uses the closed-loop control so that the smart car is able to track in safety and drive quickly on the road.
The main thesis is as follows:
First of all, for the control system it has to transform the mechanical structure. With the theory of modern vehicles, front wheel alignment parameters, gear transmission and rear differentials have been adjusted through experiments. Installation and calibration of the image sensor have been discussed too. According to analyze the impact of steering gear for the smart car system, we designed reasonable and reliable manner of the installation.
Secondly, the hardware circuits of smart car system are designed. Respectively, the core control module, power management module, image acquisition module, motor driver module, gear-driven module, and speed test module are carefully designed to ensure that the smart car has a good and stable hardware support.
Finally, in software design of the smart car system, the process of image acquisition is described. Image processing and identify algorithm have been analyzed. According to this analysis, direction control strategy and speed control strategy are researched. Comparing with the traditional PID controller, an immune adaptive PID controller by drawing on the regulation of immune feedback mechanism is designed in order to improve the tracking quality for smart car to track the target under a high speed.
论文的主要工作如下：
首先,针对控制要求对智能车系统的机械结构进行改造。结合现代汽车的相关理论,通过实验的方式对智能车底盘、前轮定位参数、齿轮传动机构、后轮及差速器进行了调整；讨论了图像传感器的安装原则与位置校正；分析了转向舵机对智能车系统产生的影响,为图像传感器与转向舵机设计出了合理、可靠的安装方式。
其次,文章对智能车系统的硬件电路进行了设计。分别对核心控制模块、电源管理模块、图像采集模块、电机驱动模块、舵机驱动模块、测速功能模块等部分的电路进行设计,保证智能车具有良好、稳定的硬件支撑。
最后,在智能车系统的软件设计中,给出了系统软件的总体架构,介绍了图像采集的流程,针对道路的特征给出了图像处理及路径识别的算法,从建模的角度对智能汽车的控制策略进行了分析和研究,在此基础上,借鉴生物免疫反馈机理并结合模糊理论,提出了一种模糊免疫自适应PID控制器,使智能车在高速行驶状态下的具有良好的目标轨迹跟踪性能。
As a carrier of many high-tech integrated, smart car plays an important role in intelligent transportation system. The smart car system uses the Freescalel6 bit microprocessor as a core control chip. The micro-controller obtains lane image information based on a digital image sensor then adjusts the model car's moving position and direction. The system uses the closed-loop control so that the smart car is able to track in safety and drive quickly on the road.
The main thesis is as follows:
First of all, for the control system it has to transform the mechanical structure. With the theory of modern vehicles, front wheel alignment parameters, gear transmission and rear differentials have been adjusted through experiments. Installation and calibration of the image sensor have been discussed too. According to analyze the impact of steering gear for the smart car system, we designed reasonable and reliable manner of the installation.
Secondly, the hardware circuits of smart car system are designed. Respectively, the core control module, power management module, image acquisition module, motor driver module, gear-driven module, and speed test module are carefully designed to ensure that the smart car has a good and stable hardware support.
Finally, in software design of the smart car system, the process of image acquisition is described. Image processing and identify algorithm have been analyzed. According to this analysis, direction control strategy and speed control strategy are researched. Comparing with the traditional PID controller, an immune adaptive PID controller by drawing on the regulation of immune feedback mechanism is designed in order to improve the tracking quality for smart car to track the target under a high speed.
引文
[1]胡海峰,忠科,徐德文.智能汽车发展研究[J].计算机应用研究,2004,21(6)：20-23.
[2]袁茵.高速启动中的智能汽车[J].电子技术,2006,33(2)：26-28.
[3]韩俊淑,韩佳文,高翔等.智能车辆的研究及发展[J].世界汽车,2003(9)：79-80.
[4]纪寿文等.国内外智能车辆研究进展[C].中国交通与探索.第三届全国交通领域青年学者会议.武汉,1999.
[5]吴怀宇,程磊,章政.大学生智能汽车设计[M].北京：电子工业出版社,2008.
[6]周允,张西文.智能汽车及智能汽车运输系统发展综述[J].陕西汽车,1999(1)：1-4.
[7]潘学军,张兆惠.基于模糊PID的智能汽车控制系统[J].控制工程,2009,16(5)：618-622.
[9]关文达.汽车构造(第二版)[M].北京：清华大学出版社,2009.
[10]卓晴,黄开胜,邵贝贝.学做智能车[M].北京：北京航空航天大学出版社,2007.
[11]伊永峰,杨勇,张立勋.TD340芯片在直流调速系统中的应用[J].国外电子元器件,2004(9)：48-50.
[12]谈英姿,沈炯,吕震中.免疫PID控制器在汽温控制系统中的应用研究[J].中国电机工程学报,2002,22(10)：148-152.
[13]丁永生,任立红.一种新颖的模糊自调整免疫反馈控制系统[J].控制与决策,2000,15(4)：443-446.
[14]章卫国,杨向忠.模糊控制理论与应用[M].西安：西北工业大学出版社,1999：49-63.
[15]张兆慧.基于微处理器的智能车控制系统开发与研究[D].大连：大连理工大学,2008.
[16]J. R.Wootton, A. Garcia-Ortiz, Intelligent Transportation System:A Global Perspe ctive[J]. Mathematical and Computer Modeling,1995,22(4):259-268.
[17]E. Dickmanns. The development of machine vision for road vehicles in the last d ecade. IEEE Intelligent Vehicle Symposium,2002, (1):268-281.
[18]陈懂,刘江,金世俊.智能小车的多传感器数据融合[J].现代电子技术,2005(6)：3-5.
[19]Minguez J, Montano L. Sensor based robot motion generation in unknown, dynamic and troublesome scenarios[J]. Robotics and Autonomous Systems,2005,52(4):290-311.
[20]吴斌华,黄卫华,程磊等.基于路径识别的智能车系统设计[J].电子技术应用,2007(3)：80-82.
[21]邵贝贝.单片机嵌入式应用的在线开发方法[M].北京：清华大学出版社,2004.
[22]尹念东,余群.基于横向预瞄偏差的驾驶员前视轨迹控制模型[J].汽车工程,2002,24(4)：287-289.
[23]胡寿松.自动控制原理[M].北京：科学出版社,2001.
[24]余永权,曾碧.单片机模糊逻辑控制[M].北京：北京航空航天大学出版社,2003.
[25]邵贝贝. Motorola(Freescale)微控制器MC68HC08原理及其嵌入式应用[M].北京：清华大学出版社,2005.
[26]薛定宇,陈阳泉.高等应用数学问题的MATLAB求解[M].北京：清华大学出版社,2004.
[27]徐向民Altium Designer快速入门[M].北京：北京航空航天大学出版社,2008.
[2]袁茵.高速启动中的智能汽车[J].电子技术,2006,33(2)：26-28.
[3]韩俊淑,韩佳文,高翔等.智能车辆的研究及发展[J].世界汽车,2003(9)：79-80.
[4]纪寿文等.国内外智能车辆研究进展[C].中国交通与探索.第三届全国交通领域青年学者会议.武汉,1999.
[5]吴怀宇,程磊,章政.大学生智能汽车设计[M].北京：电子工业出版社,2008.
[6]周允,张西文.智能汽车及智能汽车运输系统发展综述[J].陕西汽车,1999(1)：1-4.
[7]潘学军,张兆惠.基于模糊PID的智能汽车控制系统[J].控制工程,2009,16(5)：618-622.
[9]关文达.汽车构造(第二版)[M].北京：清华大学出版社,2009.
[10]卓晴,黄开胜,邵贝贝.学做智能车[M].北京：北京航空航天大学出版社,2007.
[11]伊永峰,杨勇,张立勋.TD340芯片在直流调速系统中的应用[J].国外电子元器件,2004(9)：48-50.
[12]谈英姿,沈炯,吕震中.免疫PID控制器在汽温控制系统中的应用研究[J].中国电机工程学报,2002,22(10)：148-152.
[13]丁永生,任立红.一种新颖的模糊自调整免疫反馈控制系统[J].控制与决策,2000,15(4)：443-446.
[14]章卫国,杨向忠.模糊控制理论与应用[M].西安：西北工业大学出版社,1999：49-63.
[15]张兆慧.基于微处理器的智能车控制系统开发与研究[D].大连：大连理工大学,2008.
[16]J. R.Wootton, A. Garcia-Ortiz, Intelligent Transportation System:A Global Perspe ctive[J]. Mathematical and Computer Modeling,1995,22(4):259-268.
[17]E. Dickmanns. The development of machine vision for road vehicles in the last d ecade. IEEE Intelligent Vehicle Symposium,2002, (1):268-281.
[18]陈懂,刘江,金世俊.智能小车的多传感器数据融合[J].现代电子技术,2005(6)：3-5.
[19]Minguez J, Montano L. Sensor based robot motion generation in unknown, dynamic and troublesome scenarios[J]. Robotics and Autonomous Systems,2005,52(4):290-311.
[20]吴斌华,黄卫华,程磊等.基于路径识别的智能车系统设计[J].电子技术应用,2007(3)：80-82.
[21]邵贝贝.单片机嵌入式应用的在线开发方法[M].北京：清华大学出版社,2004.
[22]尹念东,余群.基于横向预瞄偏差的驾驶员前视轨迹控制模型[J].汽车工程,2002,24(4)：287-289.
[23]胡寿松.自动控制原理[M].北京：科学出版社,2001.
[24]余永权,曾碧.单片机模糊逻辑控制[M].北京：北京航空航天大学出版社,2003.
[25]邵贝贝. Motorola(Freescale)微控制器MC68HC08原理及其嵌入式应用[M].北京：清华大学出版社,2005.
[26]薛定宇,陈阳泉.高等应用数学问题的MATLAB求解[M].北京：清华大学出版社,2004.
[27]徐向民Altium Designer快速入门[M].北京：北京航空航天大学出版社,2008.