Abstract
This paper develops a Takagi-Sugeno fuzzy observer gain design algorithm to estimate ship motion based on Automatic Identification System (AIS) data. Nowadays, AIS data is widely applied in the maritime field. To solve the problem of safety, it is necessary to accurately estimate the trajectory of ships. Firstly, a nonlinear ship dynamic system is considered to represent the dynamic behaviors of ships. In the literature, nonlinear observer design methods have been studied to estimate the ship path based on AIS data. However, the nonlinear observer design method is challenging to create directly since some dynamic ship systems are more complex. This paper represents nonlinear ship dynamic systems by the Takagi-Sugeno fuzzy model. Based on the Takagi-Sugeno fuzzy model, a fuzzy observer design method is developed to solve the problem of estimating using AIS data. Moreover, the observer gains of the fuzzy observer can be adjusted systemically by a novel algorithm. Via the proposed algorithm, a more suitable or better observer can be obtained to achieve the objectives of estimation. Corresponding to different AIS data, the better results can also be obtained individually. Finally, the simulation results are presented to show the effectiveness and applicability of the proposed fuzzy observer design method. Some comparisons with the previous nonlinear observer design method are also given in the simulations.
Highlights
IntroductionAccidents of collision often happen, especially in busy waterways with a high density of ship traffic, such as ports, inland waterways, and canals [1,2]
Based on a group of Automatic Identification System (AIS) data, the simulation results are presented to verify the efficiency of the proposed T-S fuzzy observer design method
Data advantage of the proposed T-S observer gain design algorithm is that the considered range for the average error, ηva, ηvb and ηvc can be selected by the designer flexibly
Summary
Accidents of collision often happen, especially in busy waterways with a high density of ship traffic, such as ports, inland waterways, and canals [1,2]. For investigating this problem it is necessary to consider Automatic Identification System (AIS) data. AIS data contains various types of information, including a ship’s position, speed, course, and type, among others [3,4]. The original communication of AIS data between different ships or between ships and coastal stations is limited to equipment with
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