Journal of Dalian Maritime University >
2016 , Vol. 42 >Issue 4: 1 - 6
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2016.04.001
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
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.
LIU Si-yuan , LIU Yan-cheng , FU Yu-xin , WANG Ning . Trajectory tracking control of underwater vehicles based on dynamic fuzzy neural network reaching law[J]. Journal of Dalian Maritime University, 2016 , 42(4) : 1 -6 . DOI: 10.16411/j.cnki.issn1006-7736.2016.04.001
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