In this study, to control the heading angle of a ship, which is constantly subjected to various internal and external disturbances during the voyage, an LADRC (linear active disturbance rejection control) design that focuses more on improving the disturbance removal performance was proposed. The speed rate of change of the ship’s heading angle due to the turn of the rudder angle was selected as a significant factor, and the nonlinear model of the ship’s maneuvering equation, including the steering gear, was treated as a total disturbance. It is the similar process with an LADRC design for the first-order transfer function model. At this time, the gains of the controller included in LADRC and the gains of the extended state observer were tuned to RCGAs (real-coded genetic algorithms) to minimize the integral time-weighted absolute error as an evaluation function. The simulation was performed by applying the proposed GA-LADRC controller to the heading angle control of the Mariner class vessel. In particular, it was confirmed that the proposed controller satisfactorily maintains and follows the set course even when the disturbances such as nonlinearity, modelling error, uncertainty and noise of the measurement sensor are considered.

Due to the existence of uncertainties and the unknown time variant environmental disturbances for ship course nonlinear control system, the ship course adaptive neural network robust course-keeping controller is designed by combining the backstepping technique. The neural networks (NNs) are employed for the compensating of the nonlinear term of the nonlinear ship course-keeping control system. The designed adaptive laws are designed to estimate the weights of NNs and the bounds of unknown environmental disturbances. The first order commander are introduced to solve the problem of repeating differential operations in the traditional backstepping design method, which let the designed controller easier to implement in navigation practice and structure simplicity. Theoretically, it indicates that the proposed controller can track the setting course in arbitrary expected accuracy, while keeping all control signals in the ship course control closed-loop system are uniformly ultimately bounded. Finally, the training ship of Dalian Maritime University is taken for example; simulation results illustrated the effectiveness and the robustness of the proposed controller.

파랑 중 선박의 직진성능을 시뮬레이션을 통하여 비교 검토하였다. 시뮬레이션을 구성하기위해 선박의 3자유도 조종운동방정식을 사용했으며, 선박에 가해지는 파랑강제력은 3차원 특이점 분포법을 사용하여 계산하였다. 시뮬레이션의 외란으로서 규칙파와 불규칙파를 사용하였고 최대사용타각과 제어시간지연을 제어기의 제한조건으로 설정하였다. 조종성능에 따른 직진성능을 검토하기 위해 유체력 미계수를 인위적으로 변화시킴으로서 조종성능이 다른 선박의 시뮬레이션을 구성하였다. Autopilot제어기를 사용한 일정시간의 선박의 직진 시뮬레이션을 수행하고 해당시간동안의 직진거리를 비교하여 선박의 직진성능을 검토하였다.

Generally a navigator evaluated the maneuverability of his ship by the scale of turning circle which was described only by the largest rudder angle of the port and starboard sides. But to have the sufficient knowledge of his ship's maneuvering characteristics he should consider the data about the new course keeping test, the spiral test, and the turning circle tests in accordance with the rudder angles together. In this paper the author performed the above tests to study the maneuverability of the stern trawler M.S. Pusan 404 which is a training ship of the National Fisheries University of Pusan. The obtained results are summarized as follows: 1. When the rudder angles being 5。, 10。, 20。, 30。, 35。 the advances of the starboard side turning circles were 12.8, 8.2, 4.8, 2.9, 2.7 times as large as the length of the ship, and of the port side turning circles were 13.3, 8.7, 5.4, 3.5, 2.9, time as large as the large as it. Under the same conditions the tactical diameters were 15.1, 9.7, 5.2, 3.1, 2.8 times as large as the length of the ship, for starboard side, and 17.2, 12.4, 6.4, 3.7, 3.2 times as large as it for port side. 2. As the rudder angle being increased the ratio of the advance to the tactical diameter was nearly 1 and her obeying ability was better than that of the small angle. 3. The mean values of the rates of speed reduction during the steady turning motion were 0.96, 0.92, 0.82, 0.71, 0.65 in accordance with the rudder angles. 4. The relative formulas between the distance to the new course y and the altering course x were as follows: When rudder angles being 10。, 20。, 30。, y=52.2222+1.6133x, y=48.750+0.9383x, y=39.250+0.655x respectively. 5. There was little difference of the distance to the new course between rudder angle 20。and 30。, and so it is desirable for a navigator to a navigator to use the small rudder angles unless sudden emergencies. 6. Though her rudder angle being small her course stability was good according to the spiral tests.

선박이 제한수로를 운항할 때에는 기존 심수 및 천수 중을 운항하는 선박의 조종특성과 일반적으로 다르기 때문에 선박의 안전한 항해를 위해 달라지는 선박의 조종특성 추정이 중요하다. 본 연구에서는 제한수로를 운항하는 선박의 조종성능을 추정하기 위해 조종운동 방정식과 가상 구속모형시험 시뮬레이션을 통한 유체력 미계수를 이용하여 조종성능을 추정하였다. 조종 수학 모델 중 선체, 프로펠러, 타를 분리하여 유체력을 모델링하는 방식인 모듈형(modular type) 모델에 제한수로의 영향을 고려하는 항을 추가하여 제한수로 중 조종성능을 추정 연구를 수행하였다. 제한수로 중 선체에 작용하는 유체력 미계수를 도출하기 위하여 상용 CFD 프로그램을 이용한 가상 구속모형시험 시뮬레이션을 수행하였다. 최종적으로 제한수로 중 직진 시뮬레이션과 Zig-zag 시뮬레이션을 수행하여 제한수로의 영향이 고려된 조종 시뮬레이션을 수행하였다. 특히 선박의 침로 안정성능을 평가하기 위해 Zig-zag 시험을 수행하는데, 측벽으로 인한 선박 주위의 비대칭 유동이 좌현과 우현에 압력 차이를 발생시켜 선박의 궤적에 큰 영향을 미침을 확인하였다.

In Part I(theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot and automatic selection algorithm for learning rate and number of iterations, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection of the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances will be presented.

Yaw-checking and course-keeping ability in IMO's ship manoeuvrability standards are reviewed from the viewpoint of safe navigation. Three kinds of virtual series-ships, which have different course instability, are taken as test models. The numerical simulation on Z-test is carried out in order to examine the correlation between known manoeuvrability in spiral characteristics and various kinds of overshoot angle. Then simulator experiments are executed with series-ships in a curved, narrow waterway by six operators(five active pilots and one ex-captain) in order to examine the correlation between known manoeuvrability and degree of manoeuvring difficulty. IMC criteria for yaw-checking and course-keeping ability are discussed and revised criteria are proposed.