Dynamic Positioning With Model Predictive Control
Authors:
- 19 January 2016
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Control Systems Technology
- Vol. 24 (4) , 1340-1353
Abstract
Marine vessels with dynamic positioning (DP) capability are typically equipped with sufficient number of thrusters to make them overactuated and with satellite navigation and other sensors to determine their position, heading, and velocity. An automatic control system is tasked with coordinating the thrusters to move the vessel in any desired direction and to counteract the environmental forces. The design of this control system is usually separated into several levels. First, a DP control algorithm calculates the total force and moment of force that the thruster system should produce. Then, a thrust allocation (TA) algorithm coordinates the thrusters so that the resultant force they produce matches the request from the DP control algorithm. Unless significant heuristic modifications are made, the DP control algorithm has limited information about the thruster effects such as saturations and limited rate of rotation of variable-direction thrusters, as well as systemic effects such as singular thruster configurations. The control output produced with this control architecture is therefore not always optimal, and may result in a position loss that would not have occurred with a more sophisticated control algorithm. Recent advances in computer hardware and algorithms make it possible to consider a model-predictive control (MPC) algorithm that combines positioning control and TA into a single algorithm, which should theoretically yield a near-optimal controller output. This paper explores the advantages and disadvantages of using MPC compared with the traditional algorithms.Keywords
Funding Information
- Research Council of Norway Kongsberg Maritime and Det Norske Veritas through the Knowledge Building Project Design to verification
- Centres of Excellence Funding Scheme
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