Auto disturbance rejection model predictive control for intelligent ship′ path following

被引：0
|
作者：
Yu W. [1 ,2 ]
Han S. [1 ]
Xu H. [1 ,2 ]
Wei Y. [3 ]
机构：
[1] School of Naval Architecture，Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan
[2] Key Laboratory of High Performance Ship Technology, Ministry of Education, Wuhan University of Technology, Wuhan
[3] Key Laboratory of Science and Technology on Water Jet Propulsion, Marine Design and Research Institute of China, Shanghai
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2023年 / 51卷 / 04期
关键词：
auto disturbance rejection; cascade system stability; intelligent ship; model predictive control; path following; robust compensation; underactuated ships;
D O I：
10.13245/j.hust.239269
中图分类号：
学科分类号：
摘要：
During the voyage of the intelligent ships，to resist the influence of multi-source time-varying environmental interferences and model uncertainties，the control forces are often suddenly changed，which makes it difficult for the actuators to respond，and the ship cannot accurately follow the desired path． In response to the above problem，an auto disturbance rejection model predictive control algorithm was proposed．The algorithm was based on the idea of active disturbance rejection control，a modified extended state observer (MESO) was designed to estimate the states and the total unknown disturbances of the system，and a robust compensation model predictive control (RC-MPC) algorithm was designed based on the estimated values． By using MESO，the complex ship path-following system is transformed into a linear affine system with interferences． Meanwhile，to avoid the conservative results caused by the robust model redictive control，a robust compensation algorithm for observation errors was designed，which improved the controlle′s interference suppression capability and enhanced the system′s robustness to model mismatch． Results proved that the active disturbance rejection model predictive control cascade system had global uniform asymptotic stability，and the effectiveness of the algorithm was verified by simulation experiments. © 2023 Huazhong University of Science and Technology. All rights reserved.
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页码：55 / 61
页数：6
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