Modeling And Adaptive Fuzzy Control Of Ship Dynamic Positioning System

With the progress of science and technology, research on exploitation and production in deep seas are increasing. Ship dynamic positioning systems get more and more attention of people. Ship dynamic positioning system is based on the analysis of measurement of signals, and make corresponding control actions to make the ship kept in desired position or sailing according to the desired trajectory under the complex sea states. Dynamic positioning systems is accurate, rapid and convenient operation etc, has broad application in the market and a great future. Accurate motion model of ship is the basis of dynamic system. The problem of designing dynamic systems to accomplish great control effect in the complicated sea conditions is always a hot spot of research. The model parameters identification and design and implementation of adaptive fuzzy controller for ship’s dynamic positioning system are presented in this paper. The main research work is including the following topics:Firstly, the mathematical model of ship’s dynamic positioning system is introduced. High frequency and low frequency motion models are analyzed. Because of complex sea conditions, the ships suffer the disturbance caused by wind, wave and current. The models are presented and propeller’s too based on references. Laying the foundation for system’s parameters identification and designing and implementing controller.Secondly, the methods of time domain and frequency domain are used in the ship dynamic positioning system model, in order to find the comparison of characteristics and applicability, the methods of the time domain identification method EKF(Extended Kalman Filter) as well as frequency domain method R-MISO(Reverse Multiple Input-Single Output) are taken into consideration in ship dynamic positioning system parameters identification, and carry out a comparative study of difficulty degree, convergence speed, parameter dependence, noise immunity ability and adapt to the comparison of the occasion of the methods. By the MATLAB simulation, the two algorithms are compared,the results show that the R-MISO algorithm is faster, and it doesn’t need to provide the initial value, it can be better applied to the online identification, on the other hand the EKF method processes a stronger denoising ability, however it needs a larger number of data as well as the dependence of the initial value, it can be better applied to the offline identification, this paper to some degree provides a guidance for the identification process of the ship dynamic positioning system.Finally, ship dynamic positioning experiment platform in the laboratory and control network structure of ship dynamic positioning simulation platform are introduced. And then, the theory of fuzzy approximation and two methods of adaptive fuzzy control, indirect and direct, are described in detail. Both controllers are designed and the stability analysis and the comparison of the two methods are made. Simulation experiments of the two methods are designed and implemented in the MATLAB and proves the validity.