INTELLIGENT SYSTEM CONTROL OF THE VESSEL EXECUTIVE DEVICES REDUNDANT STRUCTURE

Abstract

The article examines the issues of optimal control of vessels with redundant structures of executive devices on the example of an offshore vessel with two stern azimuth control devices (ACD) and a bow thruster. Known technical solutions for optimal control of redundant structures in the aviation, space, marine and other industries. The nearest technical solutions in the shipping are dynamic positioning systems (DP-systems) of manufacturers Navis, Marine Technologies, Rolls Royce, Transas, Consberg. The main purpose of such systems is to maintain the vessel in a given position with the help of active control during work (drilling, cable laying, cargo overloading, etc.). The main components of DP-systems are: sensors for measuring the absolute and relative position of the vessel (DGPS and Reference Systems), onboard computer with software and redundant structures of executive devices. Redundant structures in DP-systems are used to increase the reliability of the automated system. The article developed a method of using redundant structures also for optimization of control processes. The purpose of the work is to automate and optimize the processes of controling vessels with redundant structures of executive devices. On the example offshore vessel with two stern ACD and a bow thruster, optimal controls are considered that ensure: minimum energy consumption for performing DP operations, maximum control forces in the channels of longitudinal and lateral movement, which are used to move away from the platform in the presence of a downwind, as well as reconfiguration of redundant structures. The results of the experiment showed that the optimization of control processes allows to reduce energy consumption by (35–50) % and increase the control forces of the structure in the channels of longitudinal and lateral movement. At the same time, the additional load on the calculation cycle of the on-board controller, caused by the solution of optimization problems, is 25–50 ms, which is within (2.5–5) %.