Applied Sciences (May 2020)

Model Based Robust Predictive Control of Ship Roll/Yaw Motions with Input Constraints

  • Zhongjia Jin,
  • Sheng Liu,
  • Lincheng Jin,
  • Wei Chen,
  • Weilin Yang

DOI
https://doi.org/10.3390/app10103377
Journal volume & issue
Vol. 10, no. 10
p. 3377

Abstract

Read online

A robust H∞-type state feedback model predictive control (H∞-SFMPC) with input constraints is proposed to optimize the control performance during the ship sailing. Specifically, the approach employed in this paper is able to optimize the closed-loop performance with respect to an H∞-type cost function which predicts the system performance based on the actual model instead of the ideal model. As a result, the effect caused by disturbances is attenuated. The state feedback control gain for the control input of the rudder-fin joint roll/yaw control system is obtained by solving a constrained convex optimization problem in terms of linear matrix inequalities. Simulations are carried out, which reveal that the proposed approach has outstanding control performance. Furthermore, it is found that the approach also has significant robustness with respect to parameter uncertainties.

Keywords