模型预测控制
路径(计算)
控制器(灌溉)
计算机科学
控制理论(社会学)
控制(管理)
计算机网络
人工智能
农学
生物
作者
Johnson Adams,Awanish Chandra Dubey,Suresh Rajendran
标识
DOI:10.1109/oceanschennai45887.2022.9775372
摘要
This work investigates the performance of different controllers for the heading control and path following of a KVLCC2 tanker ship under wave disturbances. The guidance law is designed based on the Line of Sight (LoS) algorithm. The Maneuvering Modeling Group (MMG) Model of the KVLCC tanker is used to represent the system dynamics, whose linearized model with usual assumptions doesn't satisfy the straight line stability. An input-output based linear model is obtained by relating the rudder deflection to yaw rate using system identification method, and subsequently used for tuning the controllers. The tuned gains of the controller is then applied to the nonlinear model. The performances of PID and LQR are studied and compared with a linear Model Predictive Controller (MPC). The MPC outperforms the PID and LQR in the presence of external disturbances as well as under calm water conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI