Topic Editors

School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden
Prof. Dr. Chao Deng
The Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Dr. Shankar A. Deka
Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Dr. Jitao Li
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, China
Dr. Heling Yuan
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore

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

Abstract submission deadline
1 January 2025
Manuscript submission deadline
31 March 2025
Viewed by
9109

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
4.8 6.1 2017 17.9 Days CHF 2600 Submit
Electronics
electronics
2.9 4.7 2012 15.6 Days CHF 2400 Submit
Energies
energies
3.2 5.5 2008 16.1 Days CHF 2600 Submit
Journal of Marine Science and Engineering
jmse
2.9 3.7 2013 15.4 Days CHF 2600 Submit
Mathematics
mathematics
2.4 3.5 2013 16.9 Days CHF 2600 Submit

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Published Papers (12 papers)

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22 pages, 3049 KiB  
Article
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
Viewed by 264
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
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21 pages, 4614 KiB  
Article
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 562
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
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26 pages, 4295 KiB  
Article
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 324
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
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14 pages, 2122 KiB  
Article
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 502
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
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21 pages, 1824 KiB  
Article
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
Viewed by 683
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
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21 pages, 564 KiB  
Article
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 499
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
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25 pages, 2931 KiB  
Article
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
Viewed by 1223
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
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22 pages, 3725 KiB  
Article
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
Viewed by 642
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
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27 pages, 7822 KiB  
Article
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 684
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
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21 pages, 4163 KiB  
Article
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 812
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
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19 pages, 7297 KiB  
Article
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
Viewed by 760
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
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19 pages, 4500 KiB  
Article
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
Viewed by 850
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
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