An LQG Optimal Linear Controller for Fin Stabilizer System of Marine Vessels
QuangDuy Nguyen, Tieshan Li, Renhai Yu, Qihe Shan, Yue Wu, Jun Ning
Abstract
QuangDuy Nguyen, Tieshan Li, Renhai Yu, Qihe Shan, Yue Wu, Jun Ning
Abstract
When sailing at sea, the ship’s rolling motion will greatly affect the safety of the ship and the cargo, as well as the health of the crew. As a common means for roll reduction, active fins are usually installed on ships, and the roll reduction efficiency of these fins depends primarily on the controller. In our work, a Linear Quadratic Gaussian (LQG) optimal controller is proposed for the ship linear fin stabilizer system. Specifically, this LQG control method is combined by the linear quadratic regulator (LQR) method and the linear quadratic estimator (LQE) method, the latter of which is also known as the Kalman filter. Therefore, the separation principle is used in this paper to solve the roll reduction problem of ships, namely the LQG controller is derived by solving the predestined optimal control problem and the optimal state estimation problem. Finally, the stability and efficiency of the proposed LQG controller is validated by conducting contrast simulation with the LQR controller, and the result of which shows better performance of the designed LQG strategy.
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When sailing at sea, the ship’s rolling motion will greatly affect the safety of the ship and the cargo, as well as the health of the crew. As a common means for roll reduction, active fins are usually installed on ships, and the roll reduction efficiency of these fins depends primarily on the controller. In our work, a Linear Quadratic Gaussian (LQG) optimal controller is proposed for the ship linear fin stabilizer system. Specifically, this LQG control method is combined by the linear quadratic regulator (LQR) method and the linear quadratic estimator (LQE) method, the latter of which is also known as the Kalman filter. Therefore, the separation principle is used in this paper to solve the roll reduction problem of ships, namely the LQG controller is derived by solving the predestined optimal control problem and the optimal state estimation problem. Finally, the stability and efficiency of the proposed LQG controller is validated by conducting contrast simulation with the LQR controller, and the result of which shows better performance of the designed LQG strategy.
Key concepts: Linear-quadratic-Gaussian control, Control theory (sociology), Stabilizer (aeronautics), Fin, Optimal projection equations, Controller (irrigation), Optimal control, Linear system