Neural-Network-Based Modular Dynamic Surface Control for Surge Speed Tracking of an Unmanned Surface Vehicle Driven by a DC Motor

  • Chengcheng Meng
  • Lu Liu
  • Zhouhua PengEmail author
  • Dan WangEmail author
  • Haoliang Wang
  • Gang Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11555)


In this paper, a surge speed tracking problem for an unmanned surface vehicle (USV) driven by a direct current (DC) motor is investigated. The surge velocity tracking controller is developed based on a modular neural dynamic surface control (MNDSC) design method. Specifically, two neural-network-based identifiers are designed to identify the uncertainties existing in surge dynamics, propeller and DC motor. Then, a robust adaptive surge speed controller based on a dynamic surface control design method is designed by using the recovered unknown information from identifiers. The proposed surge velocity tracking controller is able to track any time-varying bounded velocity profiles. The stability of the closed-loop system is established based on cascade theory and input-to-state stability (ISS) theory. The effectiveness of the proposed surge speed controller for the USV is illustrated via simulations.


Surge speed tracking Neural networks Dynamic surface control DC motor Modular design 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Marine Electrical EngineeringDalian Maritime UniversityDalianPeople’s Republic of China
  2. 2.School of Information EngineeringJiangxi University of Science and TechnologyGanzhouPeople’s Republic of China

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