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Classification of sailboat Tell Tail Based on Deep Learning

Journal of Ocean University of China 2024年第3期23卷 710-720页

作者： CHANG Xiaofeng YU Jintao GAO Ying DING Hongchen LIU Yulong YU Huaming Department of Physical Education Ocean University of ChinaQingdao 266100China College of Big Data Qingdao University of Science and TechnologyQingdao 266061China College of Oceanic and Atmospheric Sciences Ocean University of ChinaQingdao 266100China

The tell tail is usually placed on the triangular sail to display the running state of the air flow on the sail surface.It is of great significance to make accurate judgement on the drift of the tell tail of the sailboat during sailing for the best sailing effect.Normally it is difficult for sailors to keep an eye for a long time on the tell sail for accurate judging its changes,affected by strong sunlight and visual fatigue.In this case,we adopt computer vision technology in hope of helping the sailors judge the changes of the tell tail in ease with ease.This paper proposes for the first time a method to classify sailboat tell tails based on deep learning and an expert guidance system,supported by a sailboat tell tail classification data set on the expert guidance system of interpreting the tell tails states in different sea wind conditions,including the feature extraction performance.Considering the expression capabilities that vary with the computational features in different visual tasks,the paper focuses on five tell tail computing features,which are recoded by an automatic encoder and classified by a SVM classifier.All experimental samples were randomly divided into five groups,and four groups were selected from each group as the training set to train the classifier.The remaining one group was used as the test set for testing.The highest resolution value of the ResNet network was 80.26%.To achieve better operational results on the basis of deep computing features obtained through the ResNet network in the experiments.The method can be used to assist the sailors in making better judgement about the tell tail changes during sailing.

关键词： tell tail sailboat classification deep learning

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sailboat navigation control system based on spiking neural networks

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Control Theory and Technology 2023年第4期21卷 489-504页

作者： Nelson Santiago Giraldo Sebastián Isaza Ricardo Andrés Velásquez Department of Electronics and Telecommunications Engineering University of Antioquia67 stMedellin050010AntioquiaColombia

In this paper,we presented the development of a navigation control system for a sailboat based on spiking neural networks(SNN).Our inspiration for this choice of network lies in their potential to achieve fast and low-energy computing on specialized hardware.To train our system,we use the modulated spike time-dependent plasticity reinforcement learning rule and a simulation environment based on the BindsNET library and USVSim simulator.Our objective was to develop a spiking neural network-based control systems that can learn policies allowing sailboats to navigate between two points by following a straight line or performing tacking and gybing strategies,depending on the sailing scenario conditions.We presented the mathematical definition of the problem,the operation scheme of the simulation environment,the spiking neural network controllers,and the control strategy used.As a result,we obtained 425 SNN-based controllers that completed the proposed navigation task,indicating that the simulation environment and the implemented control strategy work effectively.Finally,we compare the behavior of our best controller with other algorithms and present some possible strategies to improve its performance.

关键词： sailboat Control Spiking neuron Reinforcement learning BindsNet USVSim

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Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle

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浙江大学学报(英文版)A辑:应用物理与工程 2023年第9期24卷 749-761页

作者： Yujin WU Kangjian SHAO Ning WANG Zhongchao DENG Science and Technology on Underwater Vehicle Laboratory Harbin Engineering UniversityHarbin 150001China School of Marine Engineering Dalian Maritime UniversityDalian 116026China

Suffering from actuator failure and complex sideslip angle,the motion control of a sailboat becomes challenging.In this paper,an improved double finite-time observer-based line-of-sight guidance and finite-time control(IDFLOS-FC)scheme is presented for path following of sailboats.The salient features of the proposed IDFLOS-FC scheme are as follows:(1)Considering the problem of actuator failure,an actuator failure model is introduced into the dynamics model of a sailboat.(2)The time-varying sideslip angle of the sailboat is accurately observed by the double finite-time sideslip observers(DFSOs),which reduces the error in line-of-sight(LOS)guidance.(3)A radial basis function(RBF)neural network is used to fit the uncertainty of the model,and the upper bound of the sum of fault effects and external disturbances is estimated based on adaptive theory,so that the controller has accurate tracking and interference suppression.(4)According to the Lyapunov method,the system is finite-time stable.Finally,simulation was used to validate the effectiveness of the method.

关键词： sailboat Sideslip angle Sideslip angle observer Finite-time control(FC) Path following

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