Proceedings of IECON '93 - 19th Annual Conference of IEEE Industrial Electronics
DOI: 10.1109/iecon.1993.339076
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Anti-swing control of the container crane by fuzzy control

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Cited by 12 publications
(6 citation statements)
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“…They found that, while the two strategies have comparable performance, the fuzzy logic strategy is more effective in disturbance rejection. Suzuki et al (1993) proposed a similar approach that, in addition, is capable of suppressing pendulations along the travel path and changing the cable length to avoid obstacles along the path. Numerical simulations have shown that, at a low travel speed, this strategy can avoid obstacles and dampen pendulations along the path to less than 4 .…”
Section: Adaptive Controlmentioning
confidence: 99%
“…They found that, while the two strategies have comparable performance, the fuzzy logic strategy is more effective in disturbance rejection. Suzuki et al (1993) proposed a similar approach that, in addition, is capable of suppressing pendulations along the travel path and changing the cable length to avoid obstacles along the path. Numerical simulations have shown that, at a low travel speed, this strategy can avoid obstacles and dampen pendulations along the path to less than 4 .…”
Section: Adaptive Controlmentioning
confidence: 99%
“…Because they are of most interest, the power spectra of the angles of load sway ( R and T ) were selected and shown in graphs (Figs. [10][11][12][13].…”
Section: Comparison Of the Results In Frequency Domainmentioning
confidence: 99%
“…The ÿrst group consists of studies dealing with the linear motion of the suspension point (typically for overhead travelling cranes), which produces planar payload swinging (see [6][7][8][9][10][11][12][13][14][15][16][17][18] and many others, listed in [5]). The second group deals with the curved motion of the suspension point (typically for slewing cranes performing a slewing motion) and therefore with spatial load swinging (see [1][2][3][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] and many others, listed in [5]).…”
Section: Introductionmentioning
confidence: 99%
“…In literature, the controllers designed by many methods have been studied for the crane system. The fuzzy logic controller and model reference adaptive based controller including neural network based controller have been reported [1]- [3]. However, it is quite complicated to design those controllers to meet the desired performances.…”
Section: Introductionmentioning
confidence: 99%