Heading control is crucial for achieving reliable path following of autonomous ships. To ensure the control accuracy and improve the real-time performance and energy efficiency, a robust heading control algorithm based on Event-Triggered (ET) and Model Predictive Control (MPC) is studied. To reduce the frequency of steering, an ET mechanism with taking the heading error as the trigger condition is designed. Then, a predictive steering model with taking rudder as an input and heading as an output is built in combination of the trigger mechanism, a Nomoto model with disturbances. An objective function considering multiple constraints, energy consumption, and heading following performance is designed, and a dynamic optimization problem is solved with a nonlinear and hybrid optimization function. Simulation results show that the proposed event-triggered model predictive control (ETMPC) heading controller has better real-time and robustness performance than conventional MPC and PID, respectively.


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    Title :

    Robust model predictive ship heading control with event-triggered strategy


    Contributors:
    Li, Tailong (author) / Liu, Chenguang (author) / Hou, Guojiao (author) / Wu, Wenxiang (author) / Wu, Yong (author) / Chu, Xiumin (author)


    Publication date :

    2023-08-04


    Size :

    2530080 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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