STUDY ON FUZZY SELF-LEARNING CONTROL SYSTEM FOR SHIP STEERING

Fuzzy control has shown success in some application areas and emerged as analternative to some conventional control schemes. There are also some drawbacks in this approach,for example it is hard to justify the choice of fuzzy controller parameters and control rules, andcontrol precision is low, and so on. Fuzzy control is developing towards self-learning and adaptive.The ship steering motion is a nonlinear, coupling, time-delay complicated system. How to control iteffectively is the problem that many scholars are studying. In this paper, based on the repeatedcontrol of the robot, the self-learning arithmetic was worked out. The arithmetic was realized infuzzy logic way and used in cargo steering. It is the first time for the arithmetic to be used incargo steering. Our simulation results show that the arithmetic is effective and has severalpotential advantages over conventional fuzzy control. This work lays a foundation in modeling andanalyzing the fuzzy learning control system.

Adaptive back-stepping control on container ships for path following

A feedback-dominance based adaptive back-stepping(FDBAB) controller is designed to drive a container ship to follow a predefined path. In reality, current, wave and wind act on the ship and produce unwanted disturbances to the ship control system.The FDBAB controller has to compensate for such disturbances and steer the ship to track the predefined(or desired) path. The difference between the actual and the desired path along which the ship is to sail is defined as the tracking error. The FDBAB controller is built on the tracking error model which is developed based on Serret-Frenet frame transformation(SFFT). In additional to being affected by external disturbances, the ship has more outputs than inputs(under-actuated), and is inherently nonlinear.The back-stepping controller in FDBAB is used to compensate the nonlinearity. The adaptive algorithms in FDBAB is employed to approximate disturbances. Lyapunov's direct method is used to prove the stability of the control system. The FDBAB controlled system is implemented in Matlab/Simulink. The simulation results verify the effectiveness of the controller in terms of successful path tracking and disturbance rejection.

Synchro-control of Twin-rudder with Cloud Model

In ships having two rudders, an angle error exists if there is a difference in structural and electrical parameters in two steering gear systems. Such an error also results in reduced efficiency of ship maneuverability during navigation. For the sake of reducing the angle error, a synchro-ballistic control approach based on cloud model is proposed in this paper. First, the mechanism model of steering gear system is introduced. Second, the structure of synchro-control system of twin-rudder is proposed based on the master-slave control strategy. Third, synchro-ballistic controller based on cloud model is designed to solve the nonlinearity and uncertainty of system. Finally, the designed controller is tested via simulation under two different situations. The simulated results demonstrate that this method is simple and has stronger robustness against the variation of states and parameters of plants. Hence, the validity and reliability of the method is proved for synchro-control of two rudders, which is a significant engineering application.