This paper presents a framework for networked control system simulation （NCSS） to enable the analysis of the influence of network transmissions on the performance of control systems. The simulation is composed of th...This paper presents a framework for networked control system simulation （NCSS） to enable the analysis of the influence of network transmissions on the performance of control systems. The simulation is composed of the network environment simulated using the network simulator, the control system component simulation using Matlab or C/C＋＋, and an external application programming interface. To implement the plant （sensor）, controller, and actuator nodes, an agent-based design is introduced, and a multi-agent networked control system is constructed. Therefore, the network simulator 2-26 （NS-2.26） release is extended by modifying the user data protocol （UDP） common header in order to support application data transmission between network nodes. Then, modifying the network topology parameters, networked control system simulations are analyzed for different parameter changes, such as the network bandwidth, the number of plant nodes, and the sampling period. An analysis of the influence of these parameters on network-induced delays and packet drop is made. The results show that the simulation system is an effective tool for the study of networked control systems.展开更多
Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can ...Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.展开更多
文摘This paper presents a framework for networked control system simulation （NCSS） to enable the analysis of the influence of network transmissions on the performance of control systems. The simulation is composed of the network environment simulated using the network simulator, the control system component simulation using Matlab or C/C＋＋, and an external application programming interface. To implement the plant （sensor）, controller, and actuator nodes, an agent-based design is introduced, and a multi-agent networked control system is constructed. Therefore, the network simulator 2-26 （NS-2.26） release is extended by modifying the user data protocol （UDP） common header in order to support application data transmission between network nodes. Then, modifying the network topology parameters, networked control system simulations are analyzed for different parameter changes, such as the network bandwidth, the number of plant nodes, and the sampling period. An analysis of the influence of these parameters on network-induced delays and packet drop is made. The results show that the simulation system is an effective tool for the study of networked control systems.
基金supported in part by the National Natural Science Foundation of China(grant nos.61971365,61871339,62171392)Digital Fujian Province Key Laboratory of IoT Communication,Architecture and Safety Technology(grant no.2010499)+1 种基金the State Key Program of the National Natural Science Foundation of China(grant no.61731012)the Natural Science Foundation of Fujian Province of China No.2021J01004.
文摘Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.
