Fig。 11。 The goal position pi ðkÞ。
Table 6The parameters used in the simulation environment。
Model Area (m×m) Source position (m) Q Kx ; Ky rix ; riy Growth rate Initial wind velocity (m/s)
Farrell’s odor model 100 × 100 (10, 0) 5123。7618 10, 10 2, 3 0。001 (1, 0)
Table 7The parameters used in the decision process。
c1 c2 Sampling time (s) j (m) k (m)
0。8 0。2 1 40 30
Table 8The parameters used in (17) for the motion control。
b c a a x vmax (m/s) xmax (rad/s)
0。01 0。5 8 0。5 —0。5 0。8 1。57
Fig。 13。 The prediction errors。 xs is the real position of the odor source。
Table 9
The nine scenarios。
Cases The position of odor source (x; y) The initial wind speed (vx ; vy )
Case 1 (10, 0) (1, 0)
Case 2 (30, 10) (1, 0)
Case 3 (30, —20) (1, 0)
Case 4 (10, 0) (1。5, 0)
Case 5 (30, 10) (1。5, 0)
Case 6 (30, —20) (1。5, 0)
Case 7 (10, 0) (0。8, 0)
Case 8 (30, 10) (0。8, 0)
Case 9 (30, —20) (0。8, 0)
signðwy Þ· jxxi ðkÞ—hxi ðkÞj
j wy j
2 · wx is the coordinate of the goal position at the y axis if the estimated position is regarded as the origin。
Therefore, in terms of the coordinate system shown in Fig。 11, we have the goal position described by
( xxi kÞ—hxi ðkÞj
pxiðkÞ¼ hxiðkÞþ j ð 2
xxi kÞ—hxi ðkÞj
jwy j
气味源定位的有限时间粒子群算法英文文献和中文翻译(35):http://www.youerw.com/fanyi/lunwen_101498.html