As an emerging technology, digital twin is expected to bring novel application modes to the whole life cycle process of unmanned ground equipment, including research and development, design, control optimization, operation and maintenance, etc. The highly dynamic, complex, and uncertain characteristics of unmanned ground equipment and the battlefield environment also pose new challenges for digital twin technology. Starting from the new challenges faced by the digital twin of unmanned ground equipment, this paper designs a service-oriented cloud-edge-end collaborative platform architecture of the digital twin system of unmanned ground equipment, and further analyzes several key technologies supporting the implementation of the platform architecture.
{"title":"Research on Digital Twin System Platform Framework and Key Technologies of Unmanned Ground Equipment","authors":"Kunyu Wang;Lin Zhang;Cheng Xu;Han Lu;Zhen Chen;Hongbo Cheng;Rui Guo","doi":"10.23919/CSMS.2024.0009","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0009","url":null,"abstract":"As an emerging technology, digital twin is expected to bring novel application modes to the whole life cycle process of unmanned ground equipment, including research and development, design, control optimization, operation and maintenance, etc. The highly dynamic, complex, and uncertain characteristics of unmanned ground equipment and the battlefield environment also pose new challenges for digital twin technology. Starting from the new challenges faced by the digital twin of unmanned ground equipment, this paper designs a service-oriented cloud-edge-end collaborative platform architecture of the digital twin system of unmanned ground equipment, and further analyzes several key technologies supporting the implementation of the platform architecture.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598211","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141624088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The practical engineering of satellite tracking telemetry and command (TT&C) is often disturbed by unpredictable external factors, including the temporary rise in a significant quantity of satellite TT&C tasks, temporary failures and failures of some TT&C resources, and so on. To improve the adaptability and robustness of satellite TT&C systems when faced with uncertain dynamic disturbances, a hierarchical disturbance propagation mechanism and an improved contract network dynamic scheduling method for satellite TT&C resources were designed to address the dynamic scheduling problem of satellite TT&C resources. Firstly, the characteristics of the dynamic scheduling problem of satellite TT&C resources are analyzed, and a mathematical model is established with the weighted optimization objectives of maximizing the revenue from task completion and minimizing the degree of plan disturbance. Then, a bottom-up distributed dynamic collaborative scheduling framework for satellite TT&C resources is proposed, which includes a task layer, a resource layer, a central internal collaboration layer, and a central external collaboration layer. Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner, using efficient heuristic strategies in the task layer and the resource layer, respectively. We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer, the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements. Finally, a large number of simulation experiments were carried out and compared with various comparative algorithms. The results show that the proposed algorithm can effectively improve the solution effect of satellite TT&C resource dynamic scheduling problems, and has good application prospects.
{"title":"Hierarchical Disturbance Propagation Mechanism and Improved Contract Net Protocol for Satellite TT&C Resource Dynamic Scheduling","authors":"Zhiqing Xiang;Yi Gu;Xinwei Wang;Guohua Wu","doi":"10.23919/CSMS.2024.0004","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0004","url":null,"abstract":"The practical engineering of satellite tracking telemetry and command (TT&C) is often disturbed by unpredictable external factors, including the temporary rise in a significant quantity of satellite TT&C tasks, temporary failures and failures of some TT&C resources, and so on. To improve the adaptability and robustness of satellite TT&C systems when faced with uncertain dynamic disturbances, a hierarchical disturbance propagation mechanism and an improved contract network dynamic scheduling method for satellite TT&C resources were designed to address the dynamic scheduling problem of satellite TT&C resources. Firstly, the characteristics of the dynamic scheduling problem of satellite TT&C resources are analyzed, and a mathematical model is established with the weighted optimization objectives of maximizing the revenue from task completion and minimizing the degree of plan disturbance. Then, a bottom-up distributed dynamic collaborative scheduling framework for satellite TT&C resources is proposed, which includes a task layer, a resource layer, a central internal collaboration layer, and a central external collaboration layer. Dynamic disturbances are propagated layer by layer from the task layer to the central external collaboration layer in a bottom-up manner, using efficient heuristic strategies in the task layer and the resource layer, respectively. We use improved contract network algorithms in the center internal collaboration layer and the center external collaboration layer, the original scheduling plan is quickly adjusted to minimize the impact of disturbances while effectively completing dynamic task requirements. Finally, a large number of simulation experiments were carried out and compared with various comparative algorithms. The results show that the proposed algorithm can effectively improve the solution effect of satellite TT&C resource dynamic scheduling problems, and has good application prospects.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598215","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141624091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment protection. To improve the efficiency of the remanufacturing process, this work investigates an integrated scheduling problem for disassembly and reprocessing in a remanufacturing process, where product structures and uncertainty are taken into account. First, a stochastic programming model is developed to minimize the maximum completion time (makespan). Second, a Q-learning based hybrid meta-heuristic (Q-HMH) is specially devised. In each iteration, a Q-learning method is employed to adaptively choose a premium algorithm from four candidate ones, including genetic algorithm (GA), artificial bee colony (ABC), shuffled frog-leaping algorithm (SFLA), and simulated annealing (SA) methods. At last, simulation experiments are carried out by using sixteen instances with different scales, and three state-of-the-art algorithms in literature and an exact solver CPLEX are chosen for comparisons. By analyzing the results with the average relative percentage deviation (RPD) metric, we find that Q-HMH outperforms its rivals by 9.79%-26.76%. The results and comparisons verify the excellent competitiveness of Q-HMH for solving the concerned problems.
{"title":"A Q-Learning Based Hybrid Meta-Heuristic for Integrated Scheduling of Disassembly and Reprocessing Processes Considering Product Structures and Stochasticity","authors":"Fuquan Wang;Yaping Fu;Kaizhou Gao;Yaoxin Wu;Song Gao","doi":"10.23919/CSMS.2024.0007","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0007","url":null,"abstract":"Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment protection. To improve the efficiency of the remanufacturing process, this work investigates an integrated scheduling problem for disassembly and reprocessing in a remanufacturing process, where product structures and uncertainty are taken into account. First, a stochastic programming model is developed to minimize the maximum completion time (makespan). Second, a Q-learning based hybrid meta-heuristic (Q-HMH) is specially devised. In each iteration, a Q-learning method is employed to adaptively choose a premium algorithm from four candidate ones, including genetic algorithm (GA), artificial bee colony (ABC), shuffled frog-leaping algorithm (SFLA), and simulated annealing (SA) methods. At last, simulation experiments are carried out by using sixteen instances with different scales, and three state-of-the-art algorithms in literature and an exact solver CPLEX are chosen for comparisons. By analyzing the results with the average relative percentage deviation (RPD) metric, we find that Q-HMH outperforms its rivals by 9.79%-26.76%. The results and comparisons verify the excellent competitiveness of Q-HMH for solving the concerned problems.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598210","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141624145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The heightened autonomy and robust adaptability inherent in a multi-robot system have proven pivotal in disaster search and rescue, agricultural irrigation, and environmental monitoring. This study addresses the coordination of multiple robots for the surveillance of various key target positions within an area. This involves the allocation of target positions among robots and the concurrent planning of routes for each robot. To tackle these challenges, we formulate a unified optimization model addressing both target allocation and route planning. Subsequently, we introduce an adaptive memetic algorithm featuring dual-level local search strategies. This algorithm operates independently among and within robots to effectively solve the optimization problem associated with surveillance. The proposed method's efficacy is substantiated through comparative numerical experiments and simulated experiments involving diverse scales of robot teams and different target positions.
{"title":"Adaptive Memetic Algorithm with Dual-Level Local Search for Cooperative Route Planning of Multi-Robot Surveillance Systems","authors":"Hao Cheng;Jin Yi;Wei Xia;Huayan Pu;Jun Luo","doi":"10.23919/CSMS.2024.0006","DOIUrl":"https://doi.org/10.23919/CSMS.2024.0006","url":null,"abstract":"The heightened autonomy and robust adaptability inherent in a multi-robot system have proven pivotal in disaster search and rescue, agricultural irrigation, and environmental monitoring. This study addresses the coordination of multiple robots for the surveillance of various key target positions within an area. This involves the allocation of target positions among robots and the concurrent planning of routes for each robot. To tackle these challenges, we formulate a unified optimization model addressing both target allocation and route planning. Subsequently, we introduce an adaptive memetic algorithm featuring dual-level local search strategies. This algorithm operates independently among and within robots to effectively solve the optimization problem associated with surveillance. The proposed method's efficacy is substantiated through comparative numerical experiments and simulated experiments involving diverse scales of robot teams and different target positions.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598213","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141624099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dongqi Liu;Qiong Zhang;Haolan Liang;Tao Zhang;Rui Wang
The modern power system has evolved into a cyber-physical system with deep coupling of physical and information domains, which brings new security risks. Aiming at the problem that the “information-physical” cross-domain attacks with key nodes as springboards seriously threaten the safe and stable operation of power grids, a risk propagation model considering key nodes of power communication coupling networks is proposed to study the risk propagation characteristics of malicious attacks on key nodes and the impact on the system. First, combined with the complex network theory, a topological model of the power communication coupling network is established, and the key nodes of the coupling network are screened out by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method under the comprehensive evaluation index based on topological characteristics and physical characteristics. Second, a risk propagation model is established for malicious attacks on key nodes to study its propagation characteristics and analyze the state changes of each node in the coupled network. Then, two loss-causing factors: the minimum load loss ratio and transmission delay factor are constructed to quantify the impact of risk propagation on the coupled network. Finally, simulation analysis based on the IEEE 39-node system shows that the probability of node being breached $(alpha)$