Research Of Electro-hydraulic Control System Of Offshore Deck Crane Based On Fuzzy Neural Network

100t Offshore deck crane which installed on ship deck is used for loading goods near the shore or on the sea. The variation of hull dip angle which cause by the influence of wave would result in the working amplitude change of offshore deck crane, and thereby decrease the accuracy of crane working amplitude during its operation.As for the working environment of ship and crane with the characteristic of large inertia, pure lagging and nonlinear, it's difficult for adaptive system to create mathematical model, so traditional PID controller which depended on accurate modeling is not applicable to meet the requirements of varying operating condition. On the contrary, fuzzy control is suitable for processing the complex control member with inertia, lagging and non-linear; moreover, neural networks have powerful self-learning function, so the conbination of fuzzy control and neural network is capable for the working dip angle control of offshore deck crane which would lead to a improved control effect, and it is applied in this study.The accuracy of crane boom working amplitude is selected as the object of study. Trim angle sensor as well as heeling angle sensor are installed along the vertical ship centerline and horizontal ship centerline respectively. With the guarantee that the trim angle and heeling angle which are kept respectively within 2°and 5°, crane boom working amplitude is adjusted by self-adjusting control system which will make the accuracy of working amplitude retain within the allowable limit (±2%), and then adapt to the result arised by the change of hull dip angle.Fuzzy neural network controller (FNNC) which is series combined of neural network preprocessor (NNP) and fuzzy controller (FC) is applied in this study. During the simulation, the fuzzy control module and neural network control module which provided by Simulink would create signal frame structures to do simulation for system, and meanwhile analysis the adjusting effect which fuzzy neural network controller and fuzzy controller effected on the system.With its self-adaptive ability and self-learning ability, FNNC is ultilized to fulfill the control of electro-hydraulic, this control method can not only improve the control precision, but also get better reliability and powerful anti-resistant ability to meet the requirement of high stability; moreover, dynamic and static characteristic as well as robustness of the system could be precisely increased thereby to improve the working efficiency and safety of onshore deck crane and ship.