Research On Intelligent Control And Thrust Distribution For Ship Dynamic Positioning

With the advancement of the nautical science and technology as well as the ships and marine engineering, contemporary development of marine resources and sea transport has set increasingly higher standards for ship dynamic positioning, and also promoted its rapid development. Therefore, Studying dynamic positioning problem has important theoretical significance and practical value.Three degrees of freedom surface vessels are typical of nonlinear systems, they are characteristic of strong coupling, large inertia, uncertainties of model parameter as well as the disturbance to work by the outside wind, wave and flow. With the increasing demand on the positioning accuracy, the traditional PID and LQG methods do have some limitations in spite of their previous applications, thus arousing the interest of many scholars at home and abroad. And this thesis is to explore and systematically research the new control methods for ship dynamic positioning; the research work is as follows:(1) Based on MMG model theory, establish a nonlinear mathematical model of dynamically positioned vessels; verify the accuracy and validity of the model through ship’s turning simulation tests and comparative study of real ship. In order to achieve control of the ship’s course keeping, a linear ADRC method was applied to the ship motion model, and the effectiveness of this control algorithm has been proved by the simulation results.(2) Based on a simplified Norrbin nonlinear model of ship course, in view of the uncertainties of model parameter and the unknown control gain, using the RBF neural network adaptive control, a new nonlinear course keeping controller was proposed. Theoretically, first prove the existence of a continuous control law, then approximate through RBF neural network, and via Lyapunov stability theory, finally analyzes and illustrates that the consistency of all error signals of the closed-loop system for ship course keeping are ultimately bounded.(3) For surface vessels of dynamic positioning with parameter uncertainties and external disturbances, design the ship dynamic positioning control law by using bicyclic sliding-mode variable structure; achieve the design of the switching function by implementing the integral sliding mode. The outer sliding mode control law is to achieve control of the ship’s position, the outer ring controller generates a speed command and sends it to the inner ring system, and then through the inner sliding mode control law, achieve the actual speed’s tracking for speed command. Lyapunov stability has illustrated that all error signals of closed-loop system are asymptotically stable.(4) For surface vessels of dynamic positioning with parameter uncertainties and external disturbances, a RBF neural network based adaptive controller for the dynamic positioning vessel of all speed envelopes was proposed. In the process of backstepping design, a control strategy was adopted by combining RBF neural network and Nussbaum function. This method was effective to avoid the controller singularity problem and the calculation inflation problems in the process of backstepping design. Based on Lyapunov stability analysis, it’s proved that all error signals of vessels path following closed-loop system are uniformly ultimately bounded.(5) For surface vessel of dynamic positioning with parameter uncertainties and external disturbances, an adaptive output feedback controller for the dynamic positioning vessel of all speed envelopes was proposed. Firstly, a globally exponentially stable observer was designed by applying Lyapunov direct method, and then an adaptive output feedback controller was designed by adopting backstepping design method, and finally based on cascaded system theory, it’s proved that all error signals of closed-loop system of dynamic positioning vessel are asymptotically stable.(6) For a thrust with nonlinear constraints allocation optimization problem, equally scatter the dynamic equation constraint; modify traditional PSO by adding the improved inertia factor, comparison criteria as well as the interference operator; apply the improved PSO to thrust allocation strategy. The simulation result has shown that the improved PSO can make the propulsion system well track the desired command.