# Research on a Support System for Automatic Ship Navigation in Fairway
## 2 Literature  
Since the PID algorithm-based autopilot was proposed in 1922 by [PERSON] [2], many different autopilots have been studied using modern control theories to improve the course-keeping quality. For example, the autopilots were considered based on fuzzy set theory [3], the neural networks combined with back-stepping algorithm [4; 5; 6], adaptive control [7], disturbance rejection control [8], and optimal control [9]. Course-keeping autopilots with the function of ship collision avoidance was suggested in References [10; 11]. However, when there are external disturbances acting on the ship like wind, current and waves, course keeping autopilots have difficulties tracking the planned route, especially in strong disturbances. With the development of satellite guidance technology, track-keeping functions can be developed from course-keeping autopilots. For this purpose, the cross tracking error needs to be considered in the controllers. In research [12; 13], precision maneuvering and adaptive autopilots were introduced for track-keeping. In References [14; 15; 16; 17], the authors used neural networks to approach this problem. In studies [18; 19; 20], a sliding mode technique was applied through combination with a pre-filter and a high gain observer for damping the disturbance. In research [21; 22], the controllers were enhanced to perform both track-keeping and roll reduction functions in ocean waves. In comparison with others, fuzzy logic is considered a suitable approach because it has the ability to perform the wheel alteration of ship as helmsman's action with the perception and inference of input levels. As suggested in research [23], the authors proposed the fuzzy track-keeping system by suggesting the use of two sub-autopilots. In this system, first the fuzzy controller is used to control the ship course, and a second one is employed to regulate the distance off-set. For more confidence, the track-keeping of the ship was, as shown in the experiment model [24]. To enhance the adaptive nature of the fuzzy system, the research shown in Reference [25] developed a track-keeping system with a Sugeno-type and adjustable scaling factors mechanism. Recently, the authors in Reference [26] also employed fuzzy track-keeping control in ship maneuvering systems. Although the above-mentioned systems obtained significant results for track-keeping, they were only constructed under the assumption that the ship's speed is constant. This means that these track-keeping systems are only suitable on the open ocean - not for inland waterways or channels. Concurrently, many studies regarding automatic berthing systems have been published based on intelligent control theory. The process of ship berthing is carried out at low speed, when ship maneuverability is reduced significantly. Automatic ship berthing is therefore usually regarded as a difficult issue in the field of ship control. One of the most promising applications to berthing automation is neural networks, which has the ability to perform the berthing steps similarly to how it is done by the human brain. Results in automatic berthing with parallel structures were proposed in Reference [27]. Later on, ship berthing was proposed with the assistance of bow thrusters and tugboats [28]. As developed by the authors in Reference [29], a virtual window was used to create instructive data for the controller. Berthing at different ports is recorded in References [30; 31]. Another approach, which examined via the research in Reference [32], used an adaptive back-stepping control for a cruise ship under wind power. However, using a neural network or another approach for automatic ship berthing requires the ship's speed to be necessarily low. Therefore, in order to adapt to automatic ship berthing systems and track-keeping systems on the open ocean, an automatic ship navigation system in the fairway environment is necessary.