Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications

Topic Information

Dear Colleagues,

Networked autonomous systems, including unmanned surface/underwater/ground/aerial vehicles, robotics, transportation systems, power systems, and power electronics, have become useful tools to replace, help, or assist humans in various missions such as inspection and monitoring, surveillance, search, energy transmission, exploration, fault diagnosis and estimation, logistics and transportation, etc. Practical uses for such missions in both civilian and defense contexts have experienced significant growth thanks to recent technological progress in artificial intelligence (AI), computing devices, and renewable energy exploitation. With the rapid development of modern industry, determining how to further develop advanced localization, optimization, and control algorithms and apply them to actual applications has important research significance and prospects. This topic aims to present recent advances in technologies and algorithms to improve the levels of autonomy, reliability, safety, and stability of networked autonomous systems. It aims to compile new theoretical concepts, new design and analysis tools, and novel application cases. Potential topics of interest include but are not limited to the following:

• Control, optimization, or learning of multi-agent systems and related applications
• Dynamic positioning/path following/trajectory tracking/target tracking of autonomous systems including unmanned surface/underwater/ground/ aerial vehicles
• Theory and control systems with artificial intelligence using neural networks and machine learning
• Sensor network localization and indoor/outdoor localization
• Vision-based localization and formation
• Localization and control with safety guarantees
• Target localization and tracking of unmanned systems
• Data-driven techniques for network identification, modeling, and control
• Formal safety certification for large-dimensional networked systems
• Remote robotic rehabilitation and healthcare applications
• Stability and security enhancement of networked power systems with renewable energy sources
• Deep reinforcement learning for power systems security-constrained optimization
• Power electronics and converter-based power system modeling and control
• Comprehensive energy and its applications
• Fault-tolerant control, fault diagnosis, and cyber security control

Dr. Xu Fang
Prof. Dr. Chao Deng
Dr. Shankar A. Deka
Dr. Jitao Li
Dr. Heling Yuan
Topic Editors

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Drones drones	4.4	5.6	2017	21.7 Days	CHF 2600	Submit
Electronics electronics	2.6	5.3	2012	16.8 Days	CHF 2400	Submit
Energies energies	3.0	6.2	2008	17.5 Days	CHF 2600	Submit
Journal of Marine Science and Engineering jmse	2.7	4.4	2013	16.9 Days	CHF 2600	Submit
Mathematics mathematics	2.3	4.0	2013	17.1 Days	CHF 2600	Submit

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Published Papers (21 papers)

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18 pages, 4038 KiB  

Open AccessArticle

Target Trajectory Prediction-Based UAV Swarm Cooperative for Bird-Driving Strategy at Airport

by Xi Wang, Xuan Zhang, Yi Lu, Hongqiang Zhang, Zhuo Li, Pengliang Zhao and Xing Wang

Electronics 2024, 13(19), 3868; https://doi.org/10.3390/electronics13193868 - 29 Sep 2024

Viewed by 692

Abstract

This study presents a novel cooperative bird-driving strategy utilizing unmanned aerial vehicles (UAV) swarms, specifically designed for airport environments, to mitigate the risks posed by bird interference with aircraft operations. Our approach introduces a target trajectory prediction framework that integrates Long Short-Term Memory [...] Read more.

This study presents a novel cooperative bird-driving strategy utilizing unmanned aerial vehicles (UAV) swarms, specifically designed for airport environments, to mitigate the risks posed by bird interference with aircraft operations. Our approach introduces a target trajectory prediction framework that integrates Long Short-Term Memory (LSTM) networks with Kalman Filter algorithms (KF), improves the response speed of UAV swarms in bird-driving tasks, optimizes task allocation, and improves the accuracy and precision of trajectory prediction, making the entire bird-driving process more efficient and accurate. Within this framework, UAV swarms collaborate to drive birds that encroach upon designated protected areas, thereby optimizing bird-driving operations. We present a distributed collaborative bird-driving strategy to ensure effective coordination among UAV swarm members. Simulation experiments demonstrate that our strategy effectively drives dynamically changing targets, preventing them from remaining within the protected area. The proposed solution integrates dynamic target trajectory prediction using LSTM and Kalman Filter, task assignment optimization through the Hungarian algorithm, and 3D Dubins path planning. This innovative approach not only improves the operational efficiency of bird-driving in airport environments but also highlights the potential of UAV swarms to perform airborne missions in complex scenarios. Our work makes a significant contribution to the field of UAV swarm collaboration and provides practical insights for real-world applications. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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20 pages, 2370 KiB  

Open AccessArticle

Calculation Method for Sortie Mission Reliability of Shipborne Unmanned Vehicle Group

by Han Shi, Nengjian Wang and Qinhui Liu

J. Mar. Sci. Eng. 2024, 12(8), 1309; https://doi.org/10.3390/jmse12081309 - 2 Aug 2024

Viewed by 634

Abstract

To ensure unmanned vehicles can perform a sortie mission quickly, efficiently, safely and reliably after receiving the command, it is necessary to calculate the sortie mission reliability of the shipborne unmanned vehicle group before loading. Aimed at the layout and sortie characteristics of [...] Read more.

To ensure unmanned vehicles can perform a sortie mission quickly, efficiently, safely and reliably after receiving the command, it is necessary to calculate the sortie mission reliability of the shipborne unmanned vehicle group before loading. Aimed at the layout and sortie characteristics of an unmanned vehicle group, a sortie mission network model and a calculation method for sortie mission reliability are designed in this paper. Firstly, this paper uses space partition to parallel search for equal-length minimal paths based on the two-terminal network reliability. Secondly, this paper adopts the sum of disjoint products to process the equal-length minimal path set, innovatively proposing a calculation method for the sortie mission reliability of the shipborne unmanned vehicle group. Finally, the sortie mission reliability for three typical cases was calculated and compared with the Monte Carlo method. The comparative analysis indicates that the proposed method is both accurate and efficient, thereby corroborating its scientific validity and practical effectiveness. This study fills the gap in the field of sortie mission reliability and lays a theoretical foundation for subsequent research. Meanwhile, the method proposed in this paper can also be extended to the reliability calculation of a multiple-vehicle sortie mission in similar enclosed spaces. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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24 pages, 8791 KiB  

Open AccessArticle

Event-Triggered Neural Adaptive Distributed Cooperative Control for the Multi-Tug Towing of Unactuated Offshore Platform with Uncertainties and Unknown Disturbances

by Shaolong Geng, Yulong Tuo, Yuanhui Wang, Zhouhua Peng and Shasha Wang

J. Mar. Sci. Eng. 2024, 12(8), 1242; https://doi.org/10.3390/jmse12081242 - 23 Jul 2024

Cited by 1 | Viewed by 714

Abstract

An event-triggered neural adaptive cooperative control is proposed for the towing system (TS) with model parameter uncertainties and unknown disturbances. Different from ordinary multi-vessel formation control, the tugs and unactuated offshore platform in the TS are connected together by towlines, and the resultant [...] Read more.

An event-triggered neural adaptive cooperative control is proposed for the towing system (TS) with model parameter uncertainties and unknown disturbances. Different from ordinary multi-vessel formation control, the tugs and unactuated offshore platform in the TS are connected together by towlines, and the resultant tension of the towlines serves as the actual drag force for the platform. Initially, based on the radial basis function neural network (RBFNN), an adaptive RBFNN is designed to compensate unknown disturbances and model parameter uncertainties of the TS, and we use minimal learning parameter (MLP) algorithm to reduce the online learning parameters of adaptive RBFNN. Combined with dynamic surface technology and event-triggered control (ETC) mechanism, an event-triggered neural adaptive virtual controller is designed to obtain the desired drag force of the platform. According to the quadratic programming algorithm, the desired drag force is allocated as the desired tensions of towlines. Subsequently, the desired towline length and the desired position information of the tugs are obtained sequentially through the towline model and the position relationship between the tugs and the platform. Then, according to the desired positions of tugs, an event-triggered neural adaptive distributed cooperative controller is designed for achieving the multi-tug towing of the offshore platform. The ETC mechanism is introduced to reduce the communication burden within the TS and the execution frequency of the tugs’ thrusters. Finally, the stability of the closed-loop system is proven using the Lyapunov theory, and the ETC mechanism proves that no Zeno behavior occurs. The effectiveness of the ETC mechanism and the MLP-based adaptive RBFNN on the controllers of TS is verified through simulations and comparison analysis. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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12 pages, 4352 KiB  

Open AccessArticle

NSGA-III-Based Production Scheduling Optimization Algorithm for Pressure Sensor Calibration Workshop

by Ying Zou, Zuguo Chen, Shangyang Zhu and Yingcong Li

Electronics 2024, 13(14), 2844; https://doi.org/10.3390/electronics13142844 - 19 Jul 2024

Viewed by 849

Abstract

Although the NSGA-III algorithm is able to find the global optimal solution and has a good effect on the workshop scheduling optimization, the limitations in population diversity, convergence ability and local optimal solutions make it not applicable to certain situations. Thus, an improved [...] Read more.

Although the NSGA-III algorithm is able to find the global optimal solution and has a good effect on the workshop scheduling optimization, the limitations in population diversity, convergence ability and local optimal solutions make it not applicable to certain situations. Thus, an improved NSGA-III workshop scheduling optimization algorithm is proposed in this work. It aims to address these limitations of the NSGA-III algorithm in processing workshop scheduling optimization. To solve the problem of individual elimination in the traditional NSGA-III algorithm, chaotic mapping is introduced in the improved NSGA-III algorithm to generate new offspring individuals and add the selected winning individuals to the offspring population as the parent population for the next iteration. The proposed algorithm was applied to a pressure sensor calibration workshop. A comparison with the traditional NSGA-III algorithm was conducted through a simulation analysis. The results show that the proposed algorithm can obtain a better convergence performance, improve the optimization ability and avoid falling into local optimal solutions. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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14 pages, 1932 KiB  

Open AccessArticle

A Novel Voltage-Abnormal Cell Detection Method for Lithium-Ion Battery Mass Production Based on Data-Driven Model with Multi-Source Time Series Data

by Xiang Wang, Jianjun He, Fuxin Huang, Zhenjie Liu, Aibin Deng and Rihui Long

Energies 2024, 17(14), 3472; https://doi.org/10.3390/en17143472 - 15 Jul 2024

Viewed by 934

Abstract

Before leaving the factory, lithium-ion battery (LIB) cells are screened to exclude voltage-abnormal cells, which can increase the fault rate, troubleshooting difficulty, and degrade pack performance. However, the time interval to obtain the detection results through the existing voltage-abnormal cell method is too [...] Read more.

Before leaving the factory, lithium-ion battery (LIB) cells are screened to exclude voltage-abnormal cells, which can increase the fault rate, troubleshooting difficulty, and degrade pack performance. However, the time interval to obtain the detection results through the existing voltage-abnormal cell method is too long, which can seriously affect production efficiency and delay shipment, especially in the mass production of LIBs when facing a large number of time-critical orders. In this paper, we propose a data-driven voltage-abnormal cell detection method, using a fast model with simple architecture, which can detect voltage-abnormal cells based on the multi-source time series data of the LIB without a time interval. Firstly, our method transforms the different source data of a cell into a multi-source time series data representation and utilizes a recurrent-based data embedding to model the relation within it. Then, a simplified MobileNet is used to extract hidden feature from the embedded data. Finally, we detect the voltage-abnormal cells according to the hidden feature with a cell classification head. The experiment results show that the accuracy and average running time of our model on the voltage-abnormal cell detection task is 95.42% and 0.0509 ms per sample, which is a considerable improvement over existing methods. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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23 pages, 5460 KiB  

Open AccessArticle

Advancing Convergence Speed of Distributed Consensus Time Synchronization Algorithms in Unmanned Aerial Vehicle Ad Hoc Networks

by Jianfeng Wu, Kaiyuan Bai and Huabing Wu

Drones 2024, 8(7), 285; https://doi.org/10.3390/drones8070285 - 25 Jun 2024

Viewed by 1094

Abstract

Time synchronization is a critical prerequisite for unmanned aerial vehicle ad hoc networks (UANETs) to facilitate navigation and positioning, formation control, and data fusion. However, given the dynamic changes in UANETs, improving the convergence speeds of distributed consensus time synchronization algorithms with only [...] Read more.

Time synchronization is a critical prerequisite for unmanned aerial vehicle ad hoc networks (UANETs) to facilitate navigation and positioning, formation control, and data fusion. However, given the dynamic changes in UANETs, improving the convergence speeds of distributed consensus time synchronization algorithms with only local information poses a major challenge. To address this challenge, this study first establishes a convex model on the basis of graph theory and relevant theories of random matrices to approximate the original problem. Subsequently, three acceleration schemes for consensus algorithms are derived by minimizing the Frobenius norm of the iteration matrix. Additionally, this study provides a new upper bound for constant communication weights and discusses the limitations of existing metrics used to measure the convergence speeds of consensus algorithms. Finally, the proposed schemes are compared with existing ones through simulation. Our results indicate that the three proposed schemes can achieve faster convergence while maintaining high-precision synchronization in scenarios with static or known topological structures of networks. In scenarios where the topological structure of a UANET is time-varying and unknown, the scheme proposed in this paper achieves the fastest convergence speed. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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21 pages, 3352 KiB  

Open AccessArticle

Predefined-Time Platoon Control of Unmanned Aerial Vehicle with Range-Limited Communication

by Jiange Wang, Xu Fang and Xiaolei Li

Drones 2024, 8(6), 263; https://doi.org/10.3390/drones8060263 - 13 Jun 2024

Viewed by 1000

Abstract

In this paper, the predefined-time platoon control for multiple uncertain unmanned aerial vehicles (UAVs) under range-limited communication and external disturbance constraints is considered. A novel control scheme, which can guarantee communication connectivity, collision avoidance, and the predefined convergence time simultaneously, is proposed. To [...] Read more.

In this paper, the predefined-time platoon control for multiple uncertain unmanned aerial vehicles (UAVs) under range-limited communication and external disturbance constraints is considered. A novel control scheme, which can guarantee communication connectivity, collision avoidance, and the predefined convergence time simultaneously, is proposed. To achieve disturbance robustness, an observer-based distributed control law is firstly proposed with a time-varying gain. Then, a radial basis function neural network (RBFNN) with an adaptive tuning law is applied to approximate uncertainties of the system. Under the time and error transformation techniques, uniformly ultimate boundedness (UUB) stability of the closed-loop system is guaranteed within predefined convergence time. Compared with the existing results, the proposed method allows the system to have UUB within any predefined time without depending on the initial conditions or system parameters. Finally, simulation results are presented to verify the derived theorem. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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19 pages, 14326 KiB  

Open AccessArticle

A New Method of UAV Swarm Formation Flight Based on AOA Azimuth-Only Passive Positioning

by Zhen Kang, Yihang Deng, Hao Yan, Luhan Yang, Shan Zeng and Bing Li

Drones 2024, 8(6), 243; https://doi.org/10.3390/drones8060243 - 4 Jun 2024

Viewed by 1107

Abstract

UAV swarm passive positioning technology only requires the reception of electromagnetic signals to achieve the positioning and tracking of radiation sources. It avoids the active positioning strategy that requires active emission of signals and has the advantages of good concealment, long acting distance, [...] Read more.

UAV swarm passive positioning technology only requires the reception of electromagnetic signals to achieve the positioning and tracking of radiation sources. It avoids the active positioning strategy that requires active emission of signals and has the advantages of good concealment, long acting distance, and strong anti-interference ability, which has received more and more attention. In this paper, we propose a new UAV swarm formation flight method based on pure azimuth passive positioning. Specifically, we propose a two-circle positioning model, which describes the positional deviation of the receiving UAV using trigonometric functions relative to the target in polar coordinates. Furthermore, we design a two-step adjustment strategy that enables the receiving UAV to reach the target position efficiently. Based on the above design, we constructed an optimized UAV swarm formation scheme. In experiments with UAV numbers of 8 and 20, compared to the representative comparison strategy, the proposed UAV formation scheme reduces the total length of the UAV formation by 34.76% and 55.34%, respectively. It demonstrates the effectiveness of the proposed method in the application of assigning target positions to UAV swarms. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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21 pages, 2910 KiB  

Open AccessArticle

Path-Following Formation of Fixed-Wing UAVs under Communication Delay: A Vector Field Approach

by Thiem V. Pham and Thanh Dong Nguyen

Drones 2024, 8(6), 237; https://doi.org/10.3390/drones8060237 - 2 Jun 2024

Cited by 1 | Viewed by 883

Abstract

In many applications, such as atmospheric observation or disaster monitoring, cooperative control of a fleet of UAVs is crucial because it is effective in repeated tasks. In this work, we provide a workable and useful cooperative guiding algorithm for several fixed-wing UAVs to [...] Read more.

In many applications, such as atmospheric observation or disaster monitoring, cooperative control of a fleet of UAVs is crucial because it is effective in repeated tasks. In this work, we provide a workable and useful cooperative guiding algorithm for several fixed-wing UAVs to construct a path-following formation with communication delays. The two primary components of our concept are path-following (lateral guidance) and path formation (longitudinal guidance). The former is in charge of ensuring that, in the presence of wind disturbance, the lateral distance between the UAV and its targeted path converges using a well-known vector field technique. In the event of a communication delay, the latter ensures that several fixed-wing UAVs will create a predetermined formation shape. Furthermore, we provide a maximum delay bound that is dependent on the topology and a controller’s gain. Lastly, in order to confirm the viability and advantages of our suggested approach, we construct an effective platform for a hardware-in-the-loop (HIL) test. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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22 pages, 3049 KiB  

Open AccessArticle

Multi-Time-Scale Low-Carbon Economic Dispatch Method for Virtual Power Plants Considering Pumped Storage Coordination

by Junwei Zhang, Dongyuan Liu, Ling Lyu, Liang Zhang, Huachen Du, Hanzhang Luan and Lidong Zheng

Energies 2024, 17(10), 2348; https://doi.org/10.3390/en17102348 - 13 May 2024

Cited by 3 | Viewed by 878

Abstract

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy [...] Read more.

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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21 pages, 4614 KiB  

Open AccessArticle

Distributed Localization for UAV–UGV Cooperative Systems Using Information Consensus Filter

by Buqing Ou, Feixiang Liu and Guanchong Niu

Drones 2024, 8(4), 166; https://doi.org/10.3390/drones8040166 - 21 Apr 2024

Viewed by 1305

Abstract

In the evolving landscape of autonomous systems, the integration of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has emerged as a promising solution for improving the localization accuracy and operational efficiency for diverse applications. This study introduces an Information Consensus Filter [...] Read more.

In the evolving landscape of autonomous systems, the integration of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has emerged as a promising solution for improving the localization accuracy and operational efficiency for diverse applications. This study introduces an Information Consensus Filter (ICF)-based decentralized control system for UAVs, incorporating the Control Barrier Function–Control Lyapunov Function (CBF–CLF) strategy aimed at enhancing operational safety and efficiency. At the core of our approach lies an ICF-based decentralized control algorithm that allows UAVs to autonomously adjust their flight controls in real time based on inter-UAV communication. This facilitates cohesive movement operation, significantly improving the system resilience and adaptability. Meanwhile, the UAV is equipped with a visual recognition system designed for tracking and locating the UGV. According to the experiments proposed in the paper, the precision of this visual recognition system correlates significantly with the operational distance. The proposed CBF–CLF strategy dynamically adjusts the control inputs to maintain safe distances between the UAV and UGV, thereby enhancing the accuracy of the visual system. The effectiveness and robustness of the proposed system are demonstrated through extensive simulations and experiments, highlighting its potential for widespread application in UAV operational domains. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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26 pages, 4295 KiB  

Open AccessArticle

Population Game-Assisted Multi-Agent Reinforcement Learning Method for Dynamic Multi-Vehicle Route Selection

by Liping Yan and Yu Cai

Electronics 2024, 13(8), 1555; https://doi.org/10.3390/electronics13081555 - 19 Apr 2024

Viewed by 763

Abstract

To address urban traffic congestion, researchers have made various efforts to mitigate issues such as prolonged travel time, fuel wastage, and pollutant emissions. These efforts primarily involve microscopic route selection from the vehicle perspective, multi-vehicle route optimization based on traffic flow information and [...] Read more.

To address urban traffic congestion, researchers have made various efforts to mitigate issues such as prolonged travel time, fuel wastage, and pollutant emissions. These efforts primarily involve microscopic route selection from the vehicle perspective, multi-vehicle route optimization based on traffic flow information and historical data, and coordinated route optimization that models vehicle interaction as a game behavior. However, existing route selection algorithms suffer from limitations such as a lack of heuristic, low dynamicity, lengthy learning cycles, and vulnerability to multi-vehicle route conflicts. To further alleviate traffic congestion, this paper presents a Period-Stage-Round Route Selection Model (PSRRSM), which utilizes a population game between vehicles at each intersection to solve the Nash equilibrium. Additionally, a Period Learning Algorithm for Route Selection (PLA-RS) is proposed, which is based on a multi-agent deep deterministic policy gradient. The algorithm allows the agents to learn from the population game and eventually transition into autonomous learning, adapting to different decision-making roles in different periods. The PSRRSM is experimentally validated using the traffic simulation platform SUMO (Simulation of Urban Mobility) in both artificial and real road networks. The experimental results demonstrate that PSRRSM outperforms several comparative algorithms in terms of network throughput and average travel cost. This is achieved through the coordination of multi vehicle route optimization, facilitated by inter-vehicle population games and communication among road agents during training, enabling the vehicle strategies to reach a Nash equilibrium. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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14 pages, 2122 KiB  

Open AccessArticle

The Effect of Deposition Time Optimization on the Photovoltaic Performance of Sb₂Se₃ Thin-Film Solar Cells

by Jie Zhang and Shanze Li

Energies 2024, 17(8), 1937; https://doi.org/10.3390/en17081937 - 18 Apr 2024

Viewed by 1001

Abstract

Antimony selenide (Sb₂Se₃) photovoltaic thin-film materials have been recognized as suitable thin-film photovoltaic candidates for sustainable development due to the low toxicity of their constituent elements and abundant reserves. In this study, we employed the close space sublimation (CSS) [...] Read more.

Antimony selenide (Sb₂Se₃) photovoltaic thin-film materials have been recognized as suitable thin-film photovoltaic candidates for sustainable development due to the low toxicity of their constituent elements and abundant reserves. In this study, we employed the close space sublimation (CSS) method to fabricate solar cells with the FTO/SnO₂/Sb₂Se₃/P3HT/C device architecture. By optimizing the deposition time, we achieved (hk1) orientation-preferred Sb₂Se₃ films, the optimized device exhibited a peak efficiency of 5.06%. This work investigated the growth mechanism of antimony selenide using a complete characterization technique, while the experimental parameters were simulated and matched using Widget Provided Analysis of Microelectronic and Photonic Structures (wxAMPS) showing excellent potential in the deposition of optoelectronic thin films by close space sublimation. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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21 pages, 1824 KiB  

Open AccessArticle

Weak Fault Feature Extraction and Enhancement of Autonomous Underwater Vehicle Thrusters Based on Artificial Rabbits Optimization and Variational Mode Decomposition

by Dacheng Yu, Mingjun Zhang, Feng Yao and Jitao Li

J. Mar. Sci. Eng. 2024, 12(3), 455; https://doi.org/10.3390/jmse12030455 - 5 Mar 2024

Cited by 1 | Viewed by 983

Abstract

Variational Mode Decomposition (VMD) has typically been used in weak fault feature extraction in recent years. The problem analyzed in this study is weak fault feature extraction and the enhancement of AUV thrusters based on Artificial Rabbits Optimization (ARO) and VMD. First, we [...] Read more.

Variational Mode Decomposition (VMD) has typically been used in weak fault feature extraction in recent years. The problem analyzed in this study is weak fault feature extraction and the enhancement of AUV thrusters based on Artificial Rabbits Optimization (ARO) and VMD. First, we introduce ARO to solve the problem of long-running times when using VMD for weak fault feature extraction. Then, we propose a VMD denoising method based on an improved ARO algorithm to address the issue of deteriorations in the fault feature extraction effect after introducing ARO. In this method, chaotic mapping and Gaussian mutation are used to improve ARO to optimize the parameters of VMD. This leads to a reduced running time and improved fault feature extraction performance. We then perform fault feature enhancement. Due to the unsatisfactory enhancement effect of traditional modified Bayes (MB) methods for weak fault features, we introduce energy operators to transform the fault signals into the energy domain for fault feature enhancement. Finally, we add differential processing to the signal to address the issue of certain fault feature values decreasing after introducing energy operators. In the end, the effectiveness of the proposed methods is verified via pool experiments on a “Beaver II” AUV prototype. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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21 pages, 564 KiB  

Open AccessArticle

Efficient Closed-Form Solutions for Visible Light Positioning in Low-Cost IoT Devices

by Xuefen Zhu, Lufeng Mo and Xiaoping Wu

Electronics 2024, 13(3), 614; https://doi.org/10.3390/electronics13030614 - 1 Feb 2024

Viewed by 797

Abstract

Visible light positioning (VLP) has drawn great attention in the field of indoor positioning as light communication has been popularized in low-cost Internet-of-Things (IOT) devices. In this paper, we investigate the VLP problem using the received signal strength (RSS) and by only considering [...] Read more.

Visible light positioning (VLP) has drawn great attention in the field of indoor positioning as light communication has been popularized in low-cost Internet-of-Things (IOT) devices. In this paper, we investigate the VLP problem using the received signal strength (RSS) and by only considering the line-of-slight (LOS) propagation. The RSS-based VLP problem is highly nonlinear, and its solutions may be trapped in local optima without a good initial guess. To circumvent this difficulty, we propose closed-form solutions of the VLP problem considering a known or unknown user orientation. By applying the weighted least squares (WLS) method, the closed-form solutions are divided into two stages. In the stage-one WLS solution, the nonlinear VLP problem is transformed into a pseudo-linear form by introducing some auxiliary variables, which are considered to be independent of each other. The estimates of the stage-one WLS solution are further refined in the stage-two WLS solution by exploiting the constrained relationships among these defined variables. The simulation results show that the stage-two WLS solution provides good estimates for the user position and orientation. The proposed stage-two WLS solution outperforms the existing methods especially at a high signal-to-noise ratio (SNR). Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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25 pages, 2931 KiB  

Open AccessArticle

Review of the Planning and Distribution Methodologies to Locate Hydrogen Infrastructure in the Territory

by Agustín Álvarez Coomonte, Zacarías Grande Andrade, Rocio Porras Soriano and José Antonio Lozano Galant

Energies 2024, 17(1), 240; https://doi.org/10.3390/en17010240 - 2 Jan 2024

Cited by 4 | Viewed by 1790

Abstract

The member countries of the European Union (EU) have prioritized the incorporation of hydrogen as a key component of their energy objectives. As the world moves towards reducing its dependence on fossil fuels, alternative sources of energy have gained prominence. With the growing [...] Read more.

The member countries of the European Union (EU) have prioritized the incorporation of hydrogen as a key component of their energy objectives. As the world moves towards reducing its dependence on fossil fuels, alternative sources of energy have gained prominence. With the growing development of Fuel Cell Electric Vehicles (FCEVs), the establishment of an infrastructure for hydrogen production and the creation of a network of service stations have become essential. This article’s purpose is to conduct a methodical review of literature regarding the use of green hydrogen for transportation and the planning of imperative infrastructure in the territory of the EU, specifically Hydrogen Refueling Stations (HRS). In order to increase the acceptance of fuel cell vehicles, a comprehensive network of hydrogen refueling stations (HRS) must be built that enable drivers to refuel their vehicles quickly and easily, similar to gasoline or diesel vehicles. The literature review on this topic was conducted using the Web of Science database (WOS), with a variety of search terms proposed to cover all the key components of green hydrogen production and refueling infrastructure. The implementation of HRS powered by renewable energy sources is an important step in the adoption of fuel cell vehicles, and overcoming the obstacles that come with their implementation will require cooperation and innovation from governments, private businesses, and other stakeholders. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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22 pages, 3725 KiB  

Open AccessArticle

Fully Distributed Optimal Economic Dispatch for Microgrids under Directed Communication Networks Considering Time Delays

by Yuhang Zhang and Ming Ni

Energies 2023, 16(23), 7898; https://doi.org/10.3390/en16237898 - 4 Dec 2023

Cited by 2 | Viewed by 973

Abstract

Distributed generation and demand-side management are expected to play a more prominent role in future power systems. However, the increased number of generations and load demands pose new challenges to optimal energy management in a microgrid. In this paper, an economic dispatch model [...] Read more.

Distributed generation and demand-side management are expected to play a more prominent role in future power systems. However, the increased number of generations and load demands pose new challenges to optimal energy management in a microgrid. In this paper, an economic dispatch model for microgrids considering Traditional Generators (TGs), energy storage units, wind turbines (WTs), and flexible loads is established. To tackle the Economic Dispatch Problem (EDP) over directed communication networks, a fully distributed algorithm developed by leveraging a two-step state information exchange mechanism is proposed. In addition, by employing a fixed stepsize, the proposed algorithm demonstrates rapid convergence. Furthermore, our algorithm is well-suited for nonquadratic convex cost functions. Subsequently, we extend our algorithm to address imperfect communication scenarios. Even in the presence of arbitrarily large yet bounded time delays, our algorithm exhibits robustness. Finally, several numerical examples are given to verify the correctness and effectiveness of the developed results. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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27 pages, 7822 KiB  

Open AccessArticle

Specific Point in Time Excitation Control Method for Spatial Multi-Degree-of-Freedom Systems under Continuous Operation

by Shengtao Zhang and Yixiao Qin

Electronics 2023, 12(23), 4860; https://doi.org/10.3390/electronics12234860 - 1 Dec 2023

Viewed by 945

Abstract

The port container gantry crane studied in this paper is a four-degree-of-freedom spatial continuous system. In actual work, in order to make the container transfer smoothly, the response of the whole system needs to be accurately predicted and timely adjusted. The whole system [...] Read more.

The port container gantry crane studied in this paper is a four-degree-of-freedom spatial continuous system. In actual work, in order to make the container transfer smoothly, the response of the whole system needs to be accurately predicted and timely adjusted. The whole system is divided into rotary mechanism, lifting mechanism, lifting trolley mechanism, and big cart mechanism for detailed analysis. By constructing the field transfer matrix, a one-dimensional wave equation of continuous system and the Lagrange equation with redundant parameters, the response of each subsystem is solved precisely. The results of the study found that in some periods, the swing of the container was too large. In order to improve the safety and stability of transmission, an active control method of specific point in time excitation (SPE) is proposed for the first time. This method predicts the swing amplitude of the container in advance using the response results of the numerical model. When the set response interval is exceeded, the external excitation intervention can effectively inhibit the moving range of the container in the transit process. Finally, the results are compared with the simulation model to achieve the experimental purpose. It is in line with the expected experimental effect. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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21 pages, 4163 KiB  

Open AccessArticle

Command-Filter-Based Region-Tracking Control for Autonomous Underwater Vehicles with Measurement Noise

by Tu Lv, Yujia Wang, Xing Liu and Mingjun Zhang

J. Mar. Sci. Eng. 2023, 11(11), 2119; https://doi.org/10.3390/jmse11112119 - 6 Nov 2023

Cited by 1 | Viewed by 1164

Abstract

This paper investigates the AUV region-tracking control problem with measurement noise and transient and steady-state constraints. To achieve the fluctuation of AUV tracking error within an expected region while satisfying the transient and steady-state performance constraints, this paper proposes an improved nonlinear tracking [...] Read more.

This paper investigates the AUV region-tracking control problem with measurement noise and transient and steady-state constraints. To achieve the fluctuation of AUV tracking error within an expected region while satisfying the transient and steady-state performance constraints, this paper proposes an improved nonlinear tracking error transformation method. This method converts the tracking error into a new virtual error variable through nonlinear conversion, thus transforming the above performance requirements for the tracking error into boundedness requirements for the new virtual error variable. In addition, aiming at the problem of measurement noise causing strong fluctuation of the control signal, this paper proposes a finite-time AUV control method based on a two-stage command filter. This method utilizes a finite-time sliding mode differentiator to filter the virtual control signal during the derivation of the control law using the backstepping technique. In light of the signal loss incurred by two-stage filtering and its potential impact on system stability, a finite-time compensator is designed to compensate the signal loss and achieve finite-time stability of the closed-loop system. Finally, simulations conducted using ODIN AUV demonstrate that the proposed method exhibits smooth control signal and low energy consumption characteristics. Furthermore, the tracking error meets the requirements for both transient and steady-state performance, as well as regional tracking. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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19 pages, 7297 KiB  

Open AccessArticle

Proposed Adaptive Control Strategy of Modular Multilevel Converter Based on Virtual Synchronous Generator

by Dao Shi, Ling Lv, Xuesong Wang and Liang Zhang

Electronics 2023, 12(20), 4274; https://doi.org/10.3390/electronics12204274 - 16 Oct 2023

Cited by 2 | Viewed by 1129

Abstract

In the context of weak grids, vector-controlled modular multilevel converters (MMC) suffer from issues such as low inertia, low damping, and poor system stability. To address these challenges, this paper proposes a control strategy for virtual synchronous generators (VSGs) based on a fuzzy [...] Read more.

In the context of weak grids, vector-controlled modular multilevel converters (MMC) suffer from issues such as low inertia, low damping, and poor system stability. To address these challenges, this paper proposes a control strategy for virtual synchronous generators (VSGs) based on a fuzzy logic control algorithm. The conFtrol strategy leverages the capability of fuzzy algorithms to handle the fuzziness and uncertainty of input signals, enabling adaptive control of the virtual inertia and damping coefficient of the VSG, thus empowering the system with autonomous frequency and voltage regulation capabilities. When the system deviates from or approaches the stable operating point, increasing or decreasing the virtual inertia allows for dynamic adjustment of the virtual inertia and damping coefficient in response to load fluctuations during MMC operation. Through simulation verification, it is demonstrated that the proposed control method provides inertia support to the system during sudden changes in active load during MMC grid-connected operation. This control method achieves adaptive adjustment of the virtual inertia and damping coefficient, effectively enhancing system stability. The simulation results validate the effectiveness and correctness of the proposed control strategy. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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19 pages, 4500 KiB  

Open AccessArticle

An Evolutionary Game-Theoretic Approach to Unmanned Aerial Vehicle Network Target Assignment in Three-Dimensional Scenarios

by Yifan Gao, Lei Zhang, Chuanyue Wang, Xiaoyuan Zheng and Qianling Wang

Mathematics 2023, 11(19), 4196; https://doi.org/10.3390/math11194196 - 8 Oct 2023

Cited by 4 | Viewed by 1284

Abstract

Target assignment has been a hot topic of research in the academic and industrial communities for swarms of multiple unmanned aerial vehicle (multi-UAVs). Traditional methods mainly focus on cooperative target assignment in planes, and they ignore three-dimensional scenarios for the multi-UAV network target [...] Read more.

Target assignment has been a hot topic of research in the academic and industrial communities for swarms of multiple unmanned aerial vehicle (multi-UAVs). Traditional methods mainly focus on cooperative target assignment in planes, and they ignore three-dimensional scenarios for the multi-UAV network target assignment problem. This paper proposes a method for target assignment in three-dimensional scenarios based on evolutionary game theory to achieve cooperative targeting for multi-UAVs, significantly improving operational efficiency and achieving maximum utility. Firstly, we construct an evolutionary game model including game participants, a tactical strategy space, a payoff matrix, and a strategy selection probability space. Then, a multi-level information fusion algorithm is designed to evaluate the overall attack effectiveness of multi-UAVs against multiple targets. The replicator equation is leveraged to obtain the evolutionarily stable strategy (ESS) and dynamically update the optimal strategy. Finally, a typical scenario analysis and an effectiveness experiment are carried out on the RflySim platform to analyze the calculation process and verify the effectiveness of the proposed method. The results show that the proposed method can effectively provide a target assignment solution for multi-UAVs. Full article

(This article belongs to the Topic Cooperative Localization, Optimization and Control of Networked Autonomous Systems: Theories, Analysis Tools and Applications)

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