[1]QIN Beibei,CHEN Zengqiang,SUN Mingwei,et al.Active disturbance rejection control of ship course based on adaptive-network-based fuzzy inference system[J].CAAI Transactions on Intelligent Systems,2020,15(2):255-263.[doi:10.11992/tis.201809047]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
15
Number of periods:
2020 2
Page number:
255-263
Column:
学术论文—智能系统
Public date:
2020-03-05
- Title:
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Active disturbance rejection control of ship course based on adaptive-network-based fuzzy inference system
- Author(s):
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QIN Beibei1; CHEN Zengqiang1; 2; SUN Mingwei1; SUN Qinglin1
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1. College of Artificial Intelligence, Nankai University, Tianjin 300350, China;
2. Key Laboratory of Intelligent Robotics of Tianjin, Tianjin 300350, China
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- Keywords:
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course control; adaptive-network-based fuzzy inference system (ANFIS); adaptive active disturbance rejection controller; Nomoto model; linear active disturbance rejection control (LADRC); nonlinear system; gradient descent method; parameter learning
- CLC:
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TP272
- DOI:
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10.11992/tis.201809047
- Abstract:
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In actual ship course control, the model nonlinearity and parameter uncertainty of the course system when disturbed by external wind and waves bring difficulties to the design of a course controller. To solve this problem, we designed a conventional linear active disturbance rejection controller (ADRC) and two online learning ADRCs. The adaptive-network-based fuzzy inference system is used to achieve the online adjustment of the parameters of the ADRC. Moreover, the ADRCs for adaptive PD and adaptive extended state observer are designed. The simulation results show that the adaptive ADRCs have a good control effect, strong anti-interference capability, and strong robustness when the ship is subjected to external disturbance and parameter perturbation.