Research On Method Of Filtering And Position Controlling For A Dynamic Positioning Ship

Marine environment is complicated, and it is very difficult for the ship to do fixed-pointwork at sea under non-restraint conditions. The dynamic positioning technology caneffectively solve the ship security problems under fixed-point guard situations, and makingthe positioning vessels unaffected by depth limitation, and can quickly be in or out workingplace, and thus improving the mobility and accuracy of ships.This paper firstly regarded dynamic positioning ship as the research object, based on thedistributed object modeling, and under reasonable assumptions, the dynamic positioning shipthree DOF model was deduced based on the ship manoeuvring equations. And then analyzedthe environmental forces and moments such as first-order wave force, second order drift force,wind, and sea current and built the environmental force model. In addition, computersimulation was carried out to simulate the changing wind and anomaly waves according tospectral analysis.Secondly, due to the interferences from the outside environment in the dynamicpositioning process, high frequency noise exists in the measuring system. However, in theactual positioning process, these signals are useless. As a result, these high frequency noisesmust be filtered. This paper designed an adaptive linear neutral network filter according to theship characteristics, and then compared it with other adaptive filtering method, and finallychose the best one to filter the sea waves.Thirdly, this paper used single neuron adaptive PID control method to realize the shipdynamic positioning control. This paper researched on the basic idea of single neuron control,combined the neuron with traditional PID and put it into practice in the ship dynamicpositioning system and carried out computer simulation. Through the online adjustment ofPID parameters, the simulation results showed strong anti-interference ability, adaptiveability and good robustness.Finally, based on dynamic positioning system mathematical model and a single neuronPID controller, series of computer simulation experiments was carried out within and withoutthe adaptive linear neural network filter. Simulation results demonstrated that the filter caneffectively eliminate the high frequency components and has good filtering effect. And thisfilter also showed good adaptive ability and robustness.