In this study the control laws and their gains are determined based on the experimental velocity servo dynamics of a crane and hence much effort can be saved in commissioning. Expert crane operators skillfully time crane maneuvers in order to quickly eliminate load swing.
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This paper designs fuzzy anti swing controller based on the nonlinear mathematical model of bridge crane and matlabsimulink simulation was carried out.
Anti swing control bridge crane. Finally the anti swing control system is designed based on the position servo system and the swing dynamics of the crane load via the root locus method. Todays best solution is to use electromotive systems anti swing control asc on the bridge and trolley motions of the crane. Expert operator is a hardware module that intercepts pendant commands converts them into expert commands and then issues the modified commands to motor drives.
A new intelligent anti swing control scheme which combined fuzzy neural network fnn and sliding mode control smc with particle swarm optimization pso was presented for bridge crane. In recent years with the development of intelligent control theory fuzzy control theory has been applied to automatic control of the crane. When used in conjunction with an electromotive systems impulse adjustable frequency drive afds the asc prevents load swing while improving safety and reliability on each motion.
Cranewerks offers a variety of anti swing or anti sway controls. A new intelligent anti swing control scheme which combined fuzzy neural network fnn and sliding mode control smc with particle swarm optimization pso was presented for bridge crane. Expertoperator permits both novice and expert crane operators to reduce payload swing by 85 95.
Anti swing and automated controls provide safe efficient and precise control of payloads. The outputs of three fuzzy neural networks were used to approach the uncertainties of the positioning subsystem lifting rope subsystem and anti swing subsystem.
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