Comparative evaluation of modern intellectual control systems in tasks of navigation information processing
The article considers the problem of using neural technologies in ship control systems for solving a number of tasks in order to improve the forecast and refine navigation information, simulate ship dynamics to determine maneuverable elements, and build motion control systems. One of the main tasks is to obtain the coordinates of the vessel in a reckoning mode. The review is conducted precisely from the perspective of possibility of using neural network algorithms for solving this problem. A common feature of the publications reviewed in this paper is that neural network systems do not consider waves as an essential factor for calculation of the external factor. Also an important task of navigation is to obtain the coordinates of the ship's position in the autonomous mode - work out the dead reckoning. Various options for building an intelligent system have been proposed in terms of a problem for adapting the neural network system with respect to the physical characteristics of the vessel and navigation conditions. The main results are designed to obtain the coordinates of the vessel's position in the autonomous mode. From the standpoint of nonlinearity and uncertainty, it seems promising to use neural networks in the design of reckoning systems, aimed at improving the accuracy of determining the location of the vessel. The use of neural network technologies in navigation, associated with the task of building a reckoning system, occurs in two main directions. The first direction includes research in which the use of neural networks and hybrid neuro-fuzzy systems in the tasks of processing navigation information and determining vessel motion parameters is considered. The second direction is represented by studies in which the possibility of building neural network (neuro-fuzzy) systems for controlling the motion of a vessel is being studied.