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Swarm-Based Dynamic Coverage of Multi-ASV systems in the Presence of Measurement Noises

IEEE Transactions on Vehicular technology 2025年第5期74卷 7237-7250页

作者： Liu, Lu Jiao, Shijian Han, Bing Li, Tieshan Peng, Zhouhua Dalian Maritime University School of Marine Electrical Engineering Dalian116026 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China Shanghai Ship and Shipping Research Institute National Engineering Research Center of Ship & Shipping Control System Shanghai200135 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper is concerned with the dynamic coverage of multiple autonomous surface vehicles (ASVs) in the presence of static and dynamic obstacles, limited communication distance, and measurement noises. A modular control method including planning, guidance, and control is proposed. At the planning level, a swarm-based dynamic coverage strategy is developed to achieve the coverage of a given domain. Both the collision avoidance and connectivity preservation issues are solved by using artificial potential fields. At the kinematic level, novel adaptive line-of-sight guidance laws are presented based on cascade extended state observers (CESOs), such that accurate guidance signals are given by compensating for time-varying sideslip angle and suppressing measurement noises. At the kinetic level, two CESOs are developed to estimate the internal model uncertainties and external environmental disturbance, and antidisturbance kinetic control laws are designed subsequently. The proposed CESOs overcome the noises sensitivity problem of classical observers, and thus facilitate the practical implementation under measurement noises. The input-to-state stability of the closed-loop system is confirmed by the Lyapunov theory and cascade stability theory. Simulation and hardware-in-the-loop experiment results are provided to demonstrate the effectiveness of the proposed swarm-based dynamic coverage method. © 1967-2012 IEEE.

关键词： Velocity measurement

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Optimal Cooperative Secondary control for Islanded DC Microgrids via a Fully Actuated Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 405-417页

作者： Yi Yu Guo-Ping Liu Yi Huang Peng Shi IEEE Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Electrical and Mechanical Engineering the University of AdelaideSA 5005Australia Research and Innovation Centre Obuda University1034 BudapestHungary

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

关键词： DC microgrids distributed control high-order fully actuated system approach linear quadratic regulator microgrid modeling secondary control

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An improved dandelion algorithm-based mathematical model generation method for maximizing thrust of ship wind sails

An improved dandelion algorithm-based mathematical model gen...

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3rd International Conference on Smart Energy and Electrical engineering, SEEE 2024

作者： Song, Jian Zhang, Lanyong Liu, Sheng Tan, Yinchao College of Intelligent Systems Science and Engineering Harbin Engineering University Heilongjiang Harbin150001 China Research Centre of Ship Control Engineering and Intelligent Systems Engineering Technology Weihai Ocean Vocational College Shandong Weihai264300 China

Wind-assisted ships provide thrust for navigation through the ship's sails. Under different winds, the ship's sails get the maximum thrust along the course by turning to a specific azimuth. To provide the decision basis for azimuth control of ship sails and exert the effect of energy saving, this paper establishes a mathematical model of the maximum thrust of ship sails comprehensively. According to the aerodynamics of ship sails, a variety of modes are established to calculate sail thrust. An improved dandelion optimization algorithm is designed to meet the maximum thrust search requirement of ship sails. A quasi-adversarial model based on quantum computing is designed to improve initial population diversity, and an adaptive t-distribution function is introduced to improve balanced exploration and exploitation. Simulation results demonstrate the accuracy and speed of the proposed method for searching the maximum thrust. The increase in modeling accuracy has improved the energy-saving effect of sails. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Energy efficiency

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Artificial Intelligence Revolutionising the Automotive Sector:A Comprehensive Review of Current Insights, Challenges, and Future Scope

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Computers, Materials & Continua 2025年第3期82卷 3643-3692页

作者： Md Naeem Hossain MdAbdur Rahim Md Mustafizur Rahman Devarajan Ramasamy Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia Institute for Intelligent Systems Research and Innovation(ISSRI) Deakin UniversityWarun PondsVIC3216Australia Automotive Engineering Centre Universiti Malaysia Pahang Al-Sultan AbdullahPekan26600Malaysia

The automotive sector is crucial in modern society,facilitating essential transportation needs across personal,commercial,and logistical domains while significantly contributing to national economic development and employment *** transformative impact of Artificial Intelligence(AI)has revolutionised multiple facets of the automotive industry,encompassing intelligent manufacturing processes,diagnostic systems,control mechanisms,supply chain operations,customer service platforms,and traffic management *** extensive research exists on the above aspects of AI applications in automotive contexts,there is a compelling need to synthesise this knowledge comprehensively to guide and inspire future *** review introduces a novel taxonomic framework that provides a holistic perspective on AI integration into the automotive sector,focusing on next-generation AI methods and their critical implementation ***,the proposed conceptual framework for real-time condition monitoring of electric vehicle subsystems delivers actionable maintenance recommendations to stakeholders,addressing a critical gap in the *** review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation,decision-making,and safety features through the use of advanced algorithms and deep learning ***,it identifies advanced driver assistance systems,vehicle health monitoring,and predictive maintenance as the most impactful AI applications,transforming operational safety and maintenance efficiency in modern automotive *** work is beneficial to understanding the various use cases of AI in the different automotive domains,where AI maintains a state-of-the-art for sector-specific applications,providing a strong foundation for meeting Industry 4.0 needs and encouraging AI use among more nascent industry *** current work is intended to consolidate previous works while shedding som

关键词： Artificial intelligence AI techniques automotive sector autonomous vehicle decision-making VHMS

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Finite-Time Synchronization of Flux-controlled Complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Wang, Yonghuan Wang, Leimin Wu, Genping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time (wp, varpi, t) domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations. © 2023 IEEE.

关键词： Memristors

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Spatial-temporal distribution characteristics and traceability analysis of NOx emission from vehicles based on real-time automatic vehicle identification data in Guangzhou, China

Spatial-temporal distribution characteristics and traceabili...

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2023 International Conference on Smart Transportation and City engineering, STCE 2023

作者： Yang, Xinru Pian, Yuzhuang Xu, Rui Liu, Yonghong School of Intelligent Systems Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Provincial Key Laboratory of Intelligent Transportation System Guangdong Guangzhou510275 China Guangdong Provincial Engineering Research Centre for Traffic Environmental Monitoring and Control Guangdong Guangzhou510275 China

ISBN: (纸本)9781510673540

With the rapid growing of vehicle population, NOx has gradually become a key factor restricting the prevention and control of O3 pollution in China. High-resolution vehicle emission inventories are essential for the development of scientific and efficient pollution prevention and control policies. In this study, a bottom-up approach is adopted to develop a high temporal and spatial resolution vehicle NOx emission inventory for Guangzhou in 2021 based on real-time road network hourly-scale traffic data detected by 5,198 AVI devices. The study further examines the prominent emission vehicle types, emission periods, and emission hotspots in different regions (11 administrative districts, central urban areas, and non-central urban areas) to facilitate a detailed analysis and traceability of high-pollution events. The results of the study showed that the average daily NOx emission from vehicles was 196.15 t/day and the average daily emission intensity was 15.82 kg/(dayžkm). Diesel trucks, medium & heavy diesel trucks, and diesel trucks with China III or lower emission standards are the prominent vehicles with low occupancy and high emissions. In terms of spatial distribution, HDTs are the main contributors in the non-central urban areas, while heavy passenger vehicles and light duty trucks are the main contributors in the central urban areas, and buses also contribute a slightly higher percentage compared to the non-central urban areas. To meet the demand of freight transportation, the distribution of NOx emission hotspots shows a pattern of dispersion outward along the beltway network centred on Baiyun District. A more detailed traceability analysis of the high NOx emission contribution is used to assist in the development of pollution prevention policies. © 2024 SPIE.

关键词： Trucks

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An Improved Task Planning Method for Unmanned Swarms with Coupled Physical and Logical Constraints

An Improved Task Planning Method for Unmanned Swarms with Co...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Chen, Xiubin Zhang, Lei Xu, Fang Yao, Weiran School of Astronautics Harbin Institude of Technology Harbin China Wuhan 2nd Ship Design and Research Institute Wuhan China Marine Military Intelligence Innovation Institute CSSC Systems Engineering Research Institute Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy *** paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path ***-based search method is used to address path planning with physical constraints.A genetic algorithm is employed to solve multi-traveling salesman allocation problem.A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic *** experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps. © 2024 IEEE.

关键词： Genetic algorithms

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TS-NeRF: temporal and structural regularization for few-shot neural radiance fields 3

TS-NeRF: temporal and structural regularization for few-shot...

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3rd International Conference on Electronic Information engineering, Big Data, and Computer technology, EIBDCT 2024

作者： Wei, Yunpei Zhang, Weimin Li, Fangxing Guo, Ziyuan School of Mechatronical Engineering Beijing Institute of Technology Beijing China Zhengzhou Academy of Intelligent Technology Zhengzhou China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (纸本)9781510680449

For NeRF(Neural Radiance Fields), synthesizing new views from sparse inputs poses a challenge as too few inputs can lead to artifacts in the rendered views. Recent methods have tackled this issue by introducing external supervision or utilizing regularization based on priors like depth to enhance reconstruction quality. Few-shot NeRF requires additional constraint information to ensure reconstruction quality. To address this, we employed two novel regularization methods. Firstly, we introduced a loss related to view structure, reshaping multiple random points into a batch to capture the relationships between points. This structural regularization method is termed SSLIP. Additionally, studies indicate that high-frequency signals during reconstruction hinder neural networks from effectively learning low-frequency information. Based on this research, we improved the encoding of positional codes, enabling their frequency to increase with the number of training iterations, referred to as temporal regularization. This enhancement ensures NeRF effectively learns lowfrequency information during the initial training stages. Our method, building upon the current state-of-the-art ViP-NeRF model, achieved superior results on the LLFF dataset. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Image processing

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Adaptive Artificial Potential Field ship Motion Planning Based on DDPG

Adaptive Artificial Potential Field Ship Motion Planning Bas...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Chen, Huimin Liu, Chenguang He, Zhibo Zhang, Guoqing Han, Bing State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan430063 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan430063 China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan430063 China Navigation College Dalian Maritime University Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China National Engineering Research Center of Ship & Shipping Control System Shanghai200134 China

ISBN: (纸本)9789819639601

The paper presents a ship motion planning method that adjusts the attractive and repulsive gain parameters of the artificial potential field (APF) algorithm using the deep deterministic policy gradient (DDPG) algorithm, to address the challenges of parameter design and limited adaptability of traditional APF algorithms. This approach leverages the speed advantage of the APF planning algorithm and the exploration capability of the DDPG reinforcement learning algorithm. By optimizing the parameters of APF with DDPG, the local optima problem can be alleviated in complex obstacle environments. Simulation results demonstrate that the proposed motion planning algorithm can generate reasonable trajectories and exhibit strong adaptability in complex obstacle scenarios. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Motion planning

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Improved SocialVAE: A Socially-Aware ship Trajectory Prediction Method for Port Operations 2

Improved SocialVAE: A Socially-Aware Ship Trajectory Predict...

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2nd International Conference on Machine Learning, Cloud Computing, and intelligent Mining, MLCCIM 2023

作者： Gao, Wei Liu, Jin Zhi, Jiamao Wang, Junxiang College of Information Engineering Shanghai Maritime University Shanghai China China Shipping Telecommunication Co. Ltd. Shanghai Ship and Shipping Research Institute Shanghai China COSCO SHIPPING TECHNOLOGY Co. Ltd National Engineering Research Center of Ship Transportation Control Systems Shanghai China

ISBN: (纸本)9798350328530

In comparison to other regions, the traffic dynamics observed in port waters are more unclear. Given the complexity of maneuvering in multi-vessel encounter scenarios, accurate prediction of vessel trajectories in port waters is crucial for preventing accidents and improving port operations. To address the highly dynamic navigational environment and the uncertainty of navigational patterns such as heading and path selection, we propose an improved SocialV Ae(Variational Autoencoder) method. The approach use local ship observations to comprehend traffic patterns between ships in order to make ship navigation decisions. Furthermore, we present a socially aware regression module that evaluates the compatibility between past trajectory interaction codes and forecast trajectories, and then uses the resulting offsets to adjust the predicted trajectories. Additionally, for the problem of non-random missing data in port waters AIS (Automatic Identification System) data, we use a shift-corrected data interpolation method to fill in the missing values. We utilize two real AIS datasets of waterways surrounding ports to test the efficacy of our method: Copenhagen Port and Shanghai Yangshan Port. When compared to existing methods, our Improved SocialV Aedelivers excellent prediction performance on these two datasets. © 2023 IEEE.

关键词： Trajectories

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