Research on Intelligent Trajectory Control Method of Water Quality Testing Unmanned Surface Vessel

Xiong, Yan; Zhu, Hao; Lin, Pei; Wang, Jiying

doi:10.3390/jmse10091252

Cited by 10 publications

(4 citation statements)

References 28 publications

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“…The memory of embedded hardware, the accuracy and reliability of sensors and devices, and generalizability are our limitations in our developed approach and results. Some relevant issues for water quality management and testing can be considered in our future work about this article [22,23].…”

Section: Discussionmentioning

confidence: 99%

Improving Aquaculture Water Quality Using Dual-Input Fuzzy Logic Control for Ammonia Nitrogen Management

Li¹,

Lien

et al. 2023

JMSE

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In this paper, a closed-loop control system using dual-input fuzzy logic theory is proposed to improve the water quality of aquaculture. The new closed-loop control system is implemented on a Raspberry-Pi-embedded platform using Python programming. The proposed closed-loop control system integrates an RS485 function, a database transfer module, a simulating variable group function, and a trigger function import to achieve savings in human resources, power, and water consumption. The proposed closed-loop control system is equipped with an ammonia nitrogen sensor and solenoid valves for the water exchange. The experimental results demonstrate that the intelligent controller can rapidly eliminate ammonia nitrogen within the range of 2.0 ppm and maintain robust control in response to changes in ammonia nitrogen excretion from a school of fish. The experimental results provide insights into the relationship between tank capacity, water exchange solenoid valves, and ammonia nitrogen degradation time, which can be used to optimize aquaculture density and improve industrialization. The experimental results demonstrate that the savings for power and water can be achieved above 95%.

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Section: Discussionmentioning

confidence: 99%

Improving Aquaculture Water Quality Using Dual-Input Fuzzy Logic Control for Ammonia Nitrogen Management

Li¹,

Lien

et al. 2023

JMSE

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“…Subsequently, with the research and development of Li et al [63,64,65,66], the dual-mode prototype algorithm evolved into a multi-mode control method combining multiple control strategies. Since the multi-mode control method can coordinate incompatible control quality requirements such as rapidity and smoothness, accuracy and robustness, it has reached high popularity.…”

Section: Hsicmentioning

confidence: 99%

A human-simulated fuzzy membrane approach for the joint controller of walking biped robots

Liu

Zhang

Mastoi

et al. 2023

ICA

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To guarantee their locomotion, biped robots need to walk stably. The latter is achieved by a high performance in joint control. This article addresses this issue by proposing a novel human-simulated fuzzy (HF) membrane control system of the joint angles. The proposed control system, human-simulated fuzzy membrane controller (HFMC), contains several key elements. The first is an HF algorithm based on human-simulated intelligent control (HSIC). This HF algorithm incorporates elements of both multi-mode proportional-derivative (PD) and fuzzy control, aiming at solving the chattering problem of multi-mode switching while improving control accuracy. The second is a membrane architecture that makes use of the natural parallelisation potential of membrane computing to improve the real-time performance of the controller. The proposed HFMC is utilised as the joint controller for a biped robot. Numerical tests in a simulation are carried out with the planar and slope walking of a five-link biped robot, and the effectiveness of the HFMC is verified by comparing and evaluating the results of the designed HFMC, HSIC and PD. Experimental results demonstrate that the proposed HFMC not only retains the advantages of traditional PD control but also improves control accuracy, real-time performance and stability.

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“…Unmanned surface vehicles (USVs), emerging as novel waterborne unmanned platforms, possess the capabilities for long-range, prolonged operations and can be outfitted with a variety of sensors onboard to fulfill specific tasks, thus finding extensive applications in recent years in fields such as marine exploration, environmental monitoring, and patrol inspections [10,11]. Xiong et al [12] devised a USV tailored for water quality assessment and investigated its trajectory control algorithm. Sotelo-Torres et al [13] elaborated on the development of a cost-effective and practical USV for lake depth measurement.…”

Section: Introductionmentioning

confidence: 99%

Design and Testing of an Autonomous Navigation Unmanned Surface Vehicle for Buoy Inspection

Lu,

Li,

Zhang

et al. 2024

JMSE

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In response to the inefficiencies and high costs associated with manual buoy inspection, this paper presents the design and testing of an Autonomous Navigation Unmanned Surface Vehicle (USV) tailored for this purpose. The research is structured into three main components: Firstly, the hardware framework and communication system of the USV are detailed, incorporating the Robot Operating System (ROS) and additional nodes to meet practical requirements. Furthermore, a buoy tracking system utilizing the Kernelized Correlation Filter (KCF) algorithm is introduced. Secondly, buoy image training is conducted using the YOLOv7 object detection algorithm, establishing a robust model for accurate buoy state recognition. Finally, an improved Line-of-Sight (LOS) method for USV path tracking, assuming the presence of an attraction potential field around the inspected buoy, is proposed to enable a comprehensive 360-degree inspection. Experimental testing includes validation of buoy image target tracking and detection, assessment of USV autonomous navigation and obstacle avoidance capabilities, and evaluation of the enhanced LOS path tracking algorithm. The results demonstrate the USV’s efficacy in conducting practical buoy inspection missions. This research contributes insights and advancements to the fields of maritime patrol and routine buoy inspections.

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Research on Intelligent Trajectory Control Method of Water Quality Testing Unmanned Surface Vessel

Cited by 10 publications

References 28 publications

Improving Aquaculture Water Quality Using Dual-Input Fuzzy Logic Control for Ammonia Nitrogen Management

Improving Aquaculture Water Quality Using Dual-Input Fuzzy Logic Control for Ammonia Nitrogen Management

A human-simulated fuzzy membrane approach for the joint controller of walking biped robots

Design and Testing of an Autonomous Navigation Unmanned Surface Vehicle for Buoy Inspection

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