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Event-triggered neural network control of autonomous surface vehicles over wireless network

  • Research Paper
  • Special Focus on Advanced Techniques for Event-Triggered Control and Estimation
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Abstract

In this paper, an event-triggered neural network control method is proposed for autonomous surface vehicles subject to uncertainties and input constraints over wireless network. An event-triggered mechanism with three logic rules is employed to determine the wireless data transmission of states and control inputs. An event-driven neural network is applied to approximate the uncertainties using aperiodic sampled states. In addition, a predictor is employed to update the weights of neural network. An event-based bounded kinetic control law is applied to address the actuator constraints. The advantage of the proposed event-triggered neural network control approach is that the network traffic can be reduced while guaranteeing system stability and speed following performance. The closed-loop control system is proved to be input-to-state stable via cascade theory. The Zeno behavior can be avoided via the proposed event-triggered neural network control approach. A simulation example is provided to demonstrate the effectiveness of the proposed event-triggered neural network control approach for autonomous surface vehicles.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61673081, 51979020, 51909021, 51579023), Training Program for High-level Technical Talent in Transportation Industry (Grant No. 2018-030), Innovative Talents in Universities of Liaoning Province (Grant No. LR2017014), Science and Technology Fund for Distinguished Young Scholars of Dalian (Grant No. 2018RJ08), Stable Supporting Fund of Science and Technology on Underwater Vehicle Technology (Grant No. JCKYS2019604SXJQR-01), Fundamental Research Funds for the Central Universities (Grant No. 3132019319), and China Postdoctoral Science Foundation (Grant No. 2019M650086).

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Authors and Affiliations

  1. School of Marine Electrical Engineering, Dalian Maritime University, Dalian, 116026, China

    Mingao Lv, Dan Wang, Zhouhua Peng & Lu Liu

  2. School of Marine Engineering, Dalian Maritime University, Dalian, 116026, China

    Haoliang Wang

Authors
  1. Mingao Lv
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  2. Dan Wang
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  3. Zhouhua Peng
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  4. Lu Liu
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  5. Haoliang Wang
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Corresponding authors

Correspondence to Dan Wang or Zhouhua Peng.

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Lv, M., Wang, D., Peng, Z. et al. Event-triggered neural network control of autonomous surface vehicles over wireless network. Sci. China Inf. Sci. 63, 150205 (2020). https://doi.org/10.1007/s11432-019-2679-5

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  • DOI: https://doi.org/10.1007/s11432-019-2679-5

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