大连海事大学学报 >
2016 , Vol. 42 >Issue 4: 1 - 6
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2016.04.001
基于动态模糊神经趋近律的水下航行器航迹跟踪控制
收稿日期: 2016-03-11
修回日期: 2016-05-11
网络出版日期: 2016-05-11
基金资助
国家自然科学基金资助项目(51479018；51379002)；中央高校基本科研业务费专项资金资助(3132016335；3132016314).
Trajectory tracking control of underwater vehicles based on dynamic fuzzy neural network reaching law
Received date: 2016-03-11
Revised date: 2016-05-11
Online published: 2016-05-11
刘厶源 , 刘彦呈 , 付俞鑫 , 王宁 . 基于动态模糊神经趋近律的水下航行器航迹跟踪控制[J]. 大连海事大学学报, 2016 , 42(4) : 1 -6 . DOI: 10.16411/j.cnki.issn1006-7736.2016.04.001
To achieve high-accuracy trajectory tracking control of underwater vehicles with system uncertainties and external disturbances, a novel approach based on dynamic reaching law and fuzzy neural network was proposed, where the dynamic fuzzy neural network was developed to online approximate the lumped term of uncertainties and timevarying disturbances, which dynamically generates and prunes fuzzy rules based on the fuzzy firing strength. Lyapunov stability analysis proves that the proposed scheme can guarantee the stability of closedloop system and the boundedness of all signals. In addition, the tracking errors and derivative are asymptotically converge to zero. Simulation results demonstrate that the proposed scheme is able to cope with the system uncertainties and external timevarying disturbances, and achieve trajectory tracking of underwater vehicles with high accuracy.
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