The Study Of Fuzzy Intelligent Control In Dynamic Positioning System

Dynamic positioning (DP) systems have been commercially available for marine vessels since the 1960s. The conventional PID controllers cannot fit the new working condition, and more advanced control techniques based on nonlinear control and intelligent control theory were proposed by impels researchers.Fuzzy control is an intelligent control method with strong robustness, which can reach a satisfactory in the complex system. The key to a fuzzy system design lies in whether the fuzzy rule base can guarantee the completeness, robustness, and be adaptive to environment interference and uncertainty of the system. Employ the adaptive fuzzy control algorithm, on the one hand, can utilize universal approximation characteristics of the fuzzy systems; on the other hand, it can make the fuzzy system be adaptive with environment random disturbances and uncertainties.In this paper an adaptive fuzzy controller is derived with a DM rule base. Motivated by [52], an adaptive low was designed for fuzzy system. Besides, the fuzzy rule base is based on the DM fuzzy rules extraction algorithm which was proposed by [54]. The proposed adaptive fuzzy controller is proven to be uniform bounded in the sense of Lyapunov.In this paper, a nonlinear ship model and Marine environment model were introduced firstly. The first-order Markov algorithm was employed to simulate the slow change wind and second-order wave, and the research object was a supply vessel from [53] with all scale type data.Next, adaptive fuzzy algorithm was utilized to design DP controller. The adaptive law based on the Backstepping algorithm was proved to be uniform bounded in the sense of Lyapunov.At the end of this article, MATLAB simulink work was done to contrast the DP ability of the traditional PID controller and adaptive fuzzy controller. The results show that DP vessel with the adaptive fuzzy controller would be more adaptive with environmental interference and ship parametric uncertainty.