Event-triggered adaptive neural asymptotic depth tracking control of autonomous underwater vehicles

TANG Sixing, DENG Yingjie, ZHAO Yunli

doi:10.16411/j.cnki.issn1006-7736.2023.04.007

Journal of Dalian Maritime University >

2023 , Vol. 49 >Issue 4: 57 - 64

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2023.04.007

Event-triggered adaptive neural asymptotic depth tracking control of autonomous underwater vehicles

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(Department of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China)

Received date: 2023-07-17

Revised date: 2023-07-18

Accepted date: 2023-07-18

Online published: 2023-07-20

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Abstract

Aiming at high-precision depth tracking control problem of autonomous underwater vehicles (AUVs) in unknown model dynamics and environmental disturbances, an event-triggered adaptive neural asymptotic tracking controller was designed. RBF neural networks (NNs) was used to approximate the nonlinear uncertain terms, and the integral-bounded functions were incorporated into control laws and adaptive laws to achieve asymptotic convergence of tracking errors. The minimum learning parameters (MLPs) technique was adopted to compress neural weights and construct a single parameter adaptive law. The variable type event triggering condition was constructed by using the event-triggered mechanism on the controller-to-actuator channel, and avoid “Zeno” phenomenon. The inequality relationship of radial basis functions was used to solve the problem of “algebraic loop”. The Lyapunov direct method and Barbalat Lemma were used to analyze the stability of the closed-loop system and prove the asymptotic convergence of tracking errors. Simulation experiments verified that the control strategy proposed in this paper has high-precision depth tracking performance.

Key words： autonomous underwater vehicles (AUVs); depth tracking control; asymptotic tracking control; minimum learning parameters (MLPs); event-triggered control (ETC)

Cite this article

TANG Sixing, DENG Yingjie, ZHAO Yunli . Event-triggered adaptive neural asymptotic depth tracking control of autonomous underwater vehicles[J]. Journal of Dalian Maritime University, 2023 , 49(4) : 57 -64 . DOI: 10.16411/j.cnki.issn1006-7736.2023.04.007

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