Hybrid Control Architecture of an Unmanned Surface Vehicle Used for Water Quality Monitoring

Jorch Mendoza-Chok, Juan Carlos Cutipa Luque, Niel Franck Salas-Cueva, Daniel Yanyachi, Pablo Raul Yanyachi

Research output: Contribution to journalArticlepeer-review


The study of water quality in reservoirs, lakes, and coasts is an activity that mainly uses human-crewed marine vehicles to obtain site parameters such as temperature, conductivity, salinity, pH, and others. This task is facilitated by unmanned vehicles, which improve data quality in hazardous areas and minimize human exposure. This work presents a novel methodology based on systems engineering concepts and hybrid control architecture for a catamaran-class unmanned surface vehicle (USV) named EDSON-J, for remote water quality monitoring activities with payload instrumentation. Critical aspects of the project development are considered, such as requirements, risk management, design flexibility, logical decomposition, functional classification, verification, integration and validation, and technological plan. The applied methodology proposes the main components for the vehicle, a main computer running robotic operating system (ROS) with deliberative control architecture for high-level tasks and a secondary computer running finite state machine (FSM) with hierarchical control architecture for low-level tasks, executing control and navigation algorithms. The results are given through missions of water quality monitoring, attaching a multiparameter payload sonde. Manual and automatic mode controls are suitable for circular and zig-zag maneuvers and show better performance for the proposed platform, guaranteeing the specifications and requirements of the vehicle design and validating the proposed hybrid control architecture.

Original languageEnglish
Pages (from-to)112789-112798
Number of pages10
JournalIEEE Access
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2013 IEEE.


  • Unmanned surface vehicle
  • hybrid control architecture
  • remote monitoring
  • systems engineering
  • water quality


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