Study On Intelligent Control And Visual Simulation Of Ship Stabilizing Fin System

As an important system of marine engineering, ship stabilizing fins have been widely used in many different kinds of ships. Stabilizing fins have played an important role for improving ship behavior in waves, increasing operational life-span of ship, ameliorating work conditions of equipment and crew and advancing battle effectiveness of naval ship. Reducing ship roll motion is one of the important tasks of ship motion control. The researches on the purpose of intelligent control strategies and its visual simulation environment based virtual reality for ship stabilizing fin system are systemically investigated in the thesis.Generally, PID controller based anti-moment principle has been commonly adopted in ship stabilizing fin system. The performance of the controller depends mainly on natural period of ship roll motion and non-dimensional roll damping coefficient. Because of complexity, non-linearity, time-varying of ship roll motion and uncertainty of sea condition, satisfied control effect is very difficult to be obtained with conventional PID controller. The effective measure to solve the problem is that advanced control strategies should be introduced.The method of inverse mode wavelet neural network adaptive control based for ship stabilizing fin system is proposed in the thesis. Combining own multi-resolution characteristic of wavelet analysis and self-adaptation and self-learning ability and favorable dynamic nonlinear mapping characteristic of neural network, wavelet neural network possesses the advantages such as rapid learning convergence speed, high approximation accuracy, the choice of parameters (for instance, number of hidden nodes, value of net weights, etc.) based on theoretic guidance and effectively avoiding local minimum value. The simulation results show that the roll reducing effects are obviously improved, the method can overcome poor adaptability of conventional PID controller and provide better characteristics of fault tolerance and stronger nonlinear adapting ability. In the simulation studies, by introducing a signal consisting of a constant value multiplied by pseudo random binary signal as simulated input signal of wave slope angle, the built roll model gets better extensive ability for different input signals. In order to obtain the most optimal constant, avoid too heavy calculations and improve the system adaptability, the size of the constant signal can only be taken three different values since the different sea conditions can be divided into three different ranges according to the different wave height and wind speed. The simulation results indicate that satisfying effect is obtained for different sea conditions.As a practical engineering system closely related to navigation safety of ship, high control accuracy and reliability are necessarily required for ship stabilizing fin system. Although neural network control is made great progress in theoretical research, so far, most algorithms are still proved effective in simulation, the application of the control system to a practical ship completely based on neural network may take longer time. Since conventional PID control is widely adopted in the practical ship fin system, it is good choice to combine PID control with neural network to resolve the issues of practical ship fin system. Therefore, four intelligent control algorithms which integrate wavelet neural networks and PID control are presented in the thesis. In these control algorithms, neural networks are utilized in modeling of dynamic system, acted as process model or served as optimal calculation in traditional control system respectively, so choosing wavelet neural network can ensure the engineering requires such as high approximation precision, good real time characteristic, high reliability.Sea wave is the main cause of ship rolling, it is necessary to build an effective mathematic model to disturbing of sea wave for the research of ship roll reducing. Due to randomicity of sea wave, it is extraordinary difficulty to gain exact sea wave model. Thus a compositive prediction approach of sea wave based on wavelet decomposition and ANFIS model is presented in the thesis. Firstly, multilevel 1-D wavelet decomposition of irregular sea wave is completed to gain approximative regular period signals, thus, it can translate time series prediction of unregulated multi-period sea wave into time series prediction of relative simple and regular period signals. The movement trend and detail information of sea wave can be observed, the difficulty of predication can be reduced obviously. Next, the main regular period signals are predicated by using the ANFIS predication model, the final predication value can be gained by integrating the outputs of ANFIS. The simulation results illustrate the effectiveness of the method, high accuracy is acquired.Because of the complicated mechanical mechanism, serious non-linearity and time-varying of ship roll motion, precise model is hard to be obtained, the modeling and predicating methods of ship rolling time series prediction based on wavelet neural network is proposed in the thesis. Wavelet neural network combining wavelet transform time frequency localization with self-adaptation and self-learning ability and stronger robustness and generalization ability of neural network, it breakthroughs the spectrum analysis method of traditional singleness frequency. Comparing the experiment results with the simulation results based on RBF and Multi-layers Perceptron, it demonstrated that with the same network structure and the same number of hidden nodes and the sameiterating times, wavelet network possesses the characteristics of faster training and convergence speed, especially stronger approximation ability in situation of curve saltation, better predication precision has been obtained.In order to obtain realistic dynamic effect for the simulation of control for ship stabilizing fin system and realize the natural interaction between users and environment, visual simulation environment for ship stabilizing fin system is developed by using MATLAB Virtual Reality Toolbox and Virtual Dials & Gauges Blockset. It includes: ? virtual reality visual simulation of ocean waves is completed on the basis of wave spectrum analysis; ? 3-D model of ship is established by using VRML language; (D realistic-looking instruments panel is designed by simulating instruments panel of a real ship; ? the integrated system of virtual waves, virtual ship model and virtual instruments panel is set up by using MATLAB Simulink control simulation environment, the triune simulation effect is realized.