1、 1 英文翻译 翻译资料 (英文 ) Study of Control Algorithm for Smart Car System 翻译资料 (中文 ) 智能汽车系统控制算法的研究 院 系 ： 电子与信息工程学院 专 业： 电子信息工程 二一一 年 十二 月 二十八 日 2 2011 Fourth International Conference on Information and Computing Study of Control Algorithm for Smart Car System Ruixian li School of Transportation and Vehicle
2、 Engineering Shandong University of Technology Zibo, China ；Email: AbstractIn this paper, target identification and trajectory technology are analyzed. The tracking control algorithm based on the photoelectric sensors is proposed. The algorithm utilizes the errors of the location and the signal of r
3、oute as input parameters, to regulate the output angle of the steering gear. The smart car system includes the straight trajectory control algorithm, the curvy trajectory control algorithm and the S-type trajectory control algorithm according to the different characteristic of the trajectories. The
4、experiment shows that, by using the proposed algorithm, the smart car can move smoothly along the straight trajectory, the curvy trajectory and the S-type trajectory with satisfied accuracy. Index Termsphotoelectric sensor, black trajectory, smart car I. INTRODUCTION A smart car system is composed o
5、f the power supply module, the sensor module, the Direct Current (DC) driving motor module, the path identification module, the communication and debugging module and the single-chip module. In order to make the smart car move along the trajectory with reasonable speed, the detection of the path inf
6、ormation, the DC servo motor control and the driving motor control must be hung together by the single-chip. If the data of the sensor is not properly collected and identified, and the steering servo motor control has a wrong operation, the smart car will seriously shake or even deviate from the run
7、way. If the DC driving motor control is ineffective, it may also result in a slower speed in the straight line or too fast speed in the curvy trajectory. From Figure 1, we can see how the smart car system runs. Figure 1. Total control program for the smart car In this paper, we adopt the photoelectr
8、ic sensors to detect the information of the reference trajectories for a smart car to track. In order to achieve preferable stability for a smart car running along the reference trajectories, we put forward a solution according to the main control function of the smart car system, which includes the
9、 information identification of the black line, the angle control of steering gear and the speed regulation control of the driving motor. In the entire smart car system, photoelectric sensors as the smart cars eyes must accurately identify the path information to make the smart car system run steadil
10、y. The tracking control strategies include the straight line algorithm, the curvy line algorithm, the S-type line algorithm and the error-handling mechanism algorithm respectively. This tracking algorithm has the following advantages: the less collection of the discrete signal points, the anti-inter
11、ference ability to the ambient light, the short time of response and a low cost. The simulation shows that the tracking control algorithm holds similar 3 effects with those of CCD for the smart car if the layout of photoelectric sensors is arranged properly. II. THE IMPLEMENTATION OF THE TRACKING CO
12、NTROL ALGORITHM A. Photoelectric sensor layout The photoelectric sensor is made up of a series of lightemitting and light-reaccepting diodes. A black trajectory is the runway. Light intensity reflected from the black trajectory is different from that of the white trajectory. We propose a common meth
13、od which is discrete recognition algorithm based on above the principle. The diode voltage value will be sent into the microcontroller through the I/O ports . CPU determines whether or not the sensor is on the top of the marked line according to the input port voltage. The smart car system screens o
14、ut those sensors on the top of the black trajectory. At the moment, the smart car system can determine the relative location of the smart car and the path information. The layout, the number and the interval of photoelectric sensors are all closely related to the control algorithm. In order to predi
15、ct the farther distance and achieve higher efficiency, we adopt a solution that 1 type showed in Figure 2. 10 photoelectric sensors are used. Photoelectric sensors are arranged in unequal spacing. Such non-linear form has superiority and scientificalness. The black dots represent the installation po
16、sition of photoelectric sensors, symmetrical distribution on both sides. The distance between the adjacent two photoelectric sensors is set into 22, 16.5, 16.5, 16.5, 10, 16.5, 16.5, 16.5 and 22 respectively. The unit is millimeter. The circuit board is fixed on U-bracket by screw. The whole body is
17、 fixed in the front of the smart car. Figure 2. The layout of photoelectric sensors B. The Algorithm of Stable Operation System The tracking control algorithm is used to regulate the motor speed and the steering gear angle. When the photoelectric sensors between NO.3 and NO.6 are always low-level ef
18、fective, it can be claimed that photoelectric sensors have detected the straight trajectory. At the moment, the smart car will run in full speed. In this case the smart car can achieve the maximum speed. When the photoelectric sensors between NO.0 and NO.3 or between NO.6 and NO.9 are always lowleve
19、l effective, it can be claimed that photoelectric sensors have detected the S-type or curvy trajectories. In this case the smart car should slow down in advance and turn left or right. The speed of the smart car should not be too high to avoid running out. We adopt a speed limited strategy to solve
20、the problem. When the distance of tow photoelectric sensors is 22mm, the maximum speed is 3m/s. When the distance of photoelectric sensors is 16.5mm, the maximum speed is 3.3m/s. Figure 3 is the flow chart of the stable operation system. The location of a smart car is determined by the feedback valu
21、e of photoelectric sensors. The analog signal values of photoelectric sensors which have detected black line are transformed into digital signal values. The values are between 0 and 255. Then the smart car system makes a judgment to determine which sensor value is less than 80. The lesser values show that the sensors have detected the location of the black line. Then its mark bit is set into 0 in C+ program. And the CPU calculates the coordinates according to the mark bit. The smart car system will send the
