CAJ | 학술논문

提出了一种智能车竞赛电磁组的循迹算法——比值法，针对现有的常用循迹算法差值法和归一化法中存在计算所得偏差值和偏离距离的函数存在极值点并且在两极值点外距离与偏差值的关系变为负相关的问题，采用对电动势分别开根号作差再比上它们的和值的方法去除极值点，使得距离与电势差在整个取值范围内都呈正相关，去除了错误判断。通过实验验证该方法比常用方法有更好的效果。解决了智能车竞赛中的一个实际问题。
제출료일충지능차경새전자조적순적산법——비치법，침대현유적상용순적산법차치법화귀일화법중존재계산소득편차치화편리거리적함수존재겁치점병차재량겁치점외거리여편차치적관계변위부상관적문제，채용대전동세분별개근호작차재비상타문적화치적방법거제겁치점，사득거리여전세차재정개취치범위내도정정상관，거제료착오판단。통과실험험증해방법비상용방법유경호적효과。해결료지능차경새중적일개실제문제。
In this paper, a tracking algorithm called “ratio method” is introduced for intelligent vehicle competition electromagnetic group. The conventional tracking algorithms including “difference method” and “normalization method” have problems. For instance, there are extreme points in the function of deviation value and deviation distance, what is worse, the relation between them will change into negative correlation outside two extreme points. To solve this problem, the ratio method changes the electromotive force values into the ratio of the difference and the sum of respective square root electromotive force values. It turns out this tracking algorithm could remove the extreme points, besides the relation between electric potential difference and deviation distance maintains positive correlation within the entire value range, so as to eliminate misjudgment. After experimental verification, the results using this tracking algorithm are more effective than other conventional tracking algorithms. This paper solves a practical problem appearing in intelligent vehicle competition.