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Academic Journal of Computing & Information Science, 2023, 6(9); doi: 10.25236/AJCIS.2023.060913.

Ship course change control based on humanoid intelligent control


Dawei Chen, Renqiang Wang, Changhua Liu

Corresponding Author:
Renqiang Wang

College of Navigation, Jiangsu Maritime Institute, Nanjing, China


A ship heading intelligent control algorithm is designed in this paper. First, ship heading control objective is proposed by input of control rudder angle and output of ship heading; Then, according to the deviation trend of ship heading output and its ideal trajectory, information about course deviation and its rate is extracted; Finally, to achieve ship heading control, rudder angle control strategy is enactmented under specific state by adopting human thinking, reasoning and control strategy. The simulation is executed with MATLAB software, and the results show that the controllerwhich is stability has strong robustness.


Humanoid intelligent control, Control strategy, Ship motion, Heading control, Simulation

Cite This Paper

Dawei Chen, Renqiang Wang, Changhua Liu. Ship course change control based on humanoid intelligent control. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 9: 87-92. https://doi.org/10.25236/AJCIS.2023.060913.


[1] Deng Hua, Wang Renqiang, Hu Xiping, et al. Optimal control of ship heading neural network with distributed genetics. Journal of Shanghai Maritime University, 2020, 41(04): 15-19+49. 

[2] Huang Chenfeng, Zhang Xianku, Zhang Guoqing, et al. Cooperative Path Tracking Control of Autonomous Ships Based on Adaptive Disturbance Observer, Control Theory & Applications, 2020, 37(11): 2312-2320.

[3] Cai Zixing, Zhou Xiang, Li Meiyi. A novel intelligent control method evolutionary control[C]// Pro 3th World Contgress Intelligent Control & Automation. Heifei, China. 2000, 1:387-390. 

[4] Liu Shujun, Gai Xiaohua, Zhang Nanlun. Research and Simulation of Anti-Disturbance Problem on Improved Characteristic Model Algorithm of HSIC [J]. Journal of System Simulation, 2008, 6(20): 2905-2908. 

[5] Shen Zhipeng, Zhang Xiaoling. Dynamic surface adaptive control of ship trajectory tracking based on nonlinear gain recursive sliding mode, Acta Automatica Sinica, 2018, 44(10): 1833-1841. 

[6] Li Zongxuan, Bu Renxiang, Zhang Hugan. Ship path sliding mode control combining improved RBF and virtual arc, Journal of Northwestern Polytechnical University, 2021, 39(1): 216-223. 

[7] He Hongwei, Zou Zaojian, Zeng Zhihua. Adaptive neural network-sliding mode path following control for underdriven surface ships [J]. Journal of Shanghai Jiao Tong University, 2020, 54(9): 890-897. 

[8] Zhipeng Shen, Yu Wang, Haomiao Yu, Chen Guo. Finite-time adaptive tracking control of marine vehicles with complex unknowns and input saturation [J]. Ocean Engineering, 2020, 198, 106980. 

[9] Jia Xinle, Yang Yansheng. Ship motion mathematical model. Dalian Maritime University Press, 1999. 

[10] Liu Jinkun. Intelligent control [M]. Tsinghua University Press: Beijing, China, 2019, PP: 249-255. 

[11] Chen Guiqiang. Parameter Optimization and Structure Automation Design of Human-Simulated Intelligent Controller [D]. Chongqing University, 2007, 4.