Modeling an Ergatic System for Joint Control of Ship Motion

Abstract

The procedure for constructing a model of an ergatic ship motion control system is described. A ship is an object of joint control by the skipper and the control machine in the "skipper-ship" system. Anthropomorphic control is considered in the form of a sequence of descriptions of discrete control signals. The sequence is based on a set of incomplete representations of elementary motions in the state space of the "skipper-ship" system. The relationship between the parameters of the ship movement and the state of the human-machine interface controls in the wheel-house in order to move on different parts of the trajectory in the state space is taken into account. The possibility of applying the model at all three levels of motion control: targeting, planning, and implementation, is shown. Descriptions of incomplete representations of elementary movements of a ship with two propellers and rudder are given. The description is given in the nine-dimensional state space using normal systems of ordinary differential equations. The set includes 27 incomplete representations of elementary movements. It defines the maximum number of 702 pairwise different signals for discrete state control of the "skipper-ship" system. Techniques and examples of reducing the number of signals for discrete state control of the "skipper-ship" system are shown. They are combined into use cases-templates with reference to the goals of traffic management based on the experience of navigation. Due to templates, in the implementation of anthropomorphic control, it is easier to solve the problems of its design at the levels of target designation, planning and performance. The advantages of the model are noted. They are expressed in the fact that at predicting the vessel movement relative to any point of the trajectory in the state space of the system, it is necessary and sufficient to have the values of the phase coordinates only for this point as the initial conditions for integrating the differential equations of the model and not refer to the movement "in the past". The model provides an opportunity to analyze the behavior of the vessel under the influence of internal and external uncertainties when performing joint control. The model allows you to perform optimization by solving a finitedimensional mathematical programming problem.