Application of H infinite control to ship steering system

Because the general object of ship steering control system is singular, the state Of rudder force and the state of disturbance are separated, and the generalized yaw output disturhance is obtained. Furthermore, singular system control problem of ship yaw and sway coupled system is transferred into nonsingular standard control problem. Then according to the linear fractional denoting algorithm of the rational function parameter perturbation system, the Linear Fractional Transform （LFT） model of yaw and sway coupled motion is solved, which is used to design the ship steering robust control system. For the ship steering system with the uncertain parameters, the robust control law is designed based on H^∞ μ-synthesis. And the robust performance of the system is analyzed and the simulation validation is made. Simulation results show that the designed control system has excellent control effect and robustness.

On the Existence of an Optimal Control of Ship Automatic Steering Instruments

The existence of linear quadratic optimal control of ship automatic steering instruments is studied. Firstly, the sufficient conditions for the quadratic integrability of the solutions of linear second order time-variant differential equations are developed. Secondly, the optimal control form of the ship automatic steering instrument is obtained by using the dynamic programming method, which guarantees a minimal ship sway range, during long-distance navigation, by using as little energy as possible. Finally, based on the above mentioned sufficient conditions, the conditions for the realization of optimal control are obtained, which provides a foundation for choosing the weighted coefficients for optimal control in engineering.

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.

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.

Application of Support Vector Machine to Ship Steering

System identification is an effective way for modeling ship manoeuvring motion and ship manoeuvrability prediction. Support vector machine is proposed to identify the manoeuvring indices in four different response models of ship steering motion, including the first order linear, the first order nonlinear, the second order linear and the second order nonlinear models. Predictions of manoeuvres including trained samples by using the identified parameters are compared with the results of free-running model tests. It is discussed that the different four categories are consistent with each other both analytically and numerically. The generalization of the identified model is verified by predicting different untrained manoeuvres. The simulations and comparisons demonstrate the validity of the proposed method.

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.

A Hybrid Firefly Algorithm for Optimizing Fractional Proportional-Integral-Derivative Controller in Ship Steering

In this paper, a new algorithm which integrates the powerful firefly Mgorithm （FA） and the ant colony optimization （ACO） has been used in tracking control of ship steering for optimization of fractional-order proportional-integral-derivative （FOPID） controller gains. Particle swarm optimization （PSO） algorithm is also used to optimize FOPID controllers, and their performances are compared. It is found that FA optimized FOPID controller gives better performance than others. Sensitivity analysis has been carried out to see the robustness of optimum FOPID gains obtained at nominal conditions to wide changes in system parameters, and the optimum FOPID gains need not be reset for wide changes in system parameters.