About this Research Topic
Recent years have seen an increased interest in estimation and cooperative control for networked systems due to their use in distributed sensor networks, electric power networks, unmanned mobile swarms, and intelligent vehicle formation. One of the paramount criteria for designing a better controller in networked systems is the consensus rate. In this regard, the finite-time protocols have aroused a large number of research interests and proven their success.
However, the finite-time control, estimation, and optimization of networked systems face great challenges. On one hand, in the existing results, the finite-time zero-error convergence is dependent on the initial conditions and the exact network topology. How to achieve distributed control quickly with few constraints on the communication topologies and high accuracy is still an open problem. On the other hand, due to the large scale of networks, it is very important to estimate the state of nodes in the network effectively. Distributed state observer is widely used in a networked system to estimate the state of the tracking targets via the communication topology. It remains a big challenge to design a distributed finite-time zero-error observer on generally directed topologies, whose needed time interval is independent of the initial states of the MAS as well as network algebraic connectivity. Moreover, distributed finite-time network optimization, searching for the global optimal solution within a finite time interval while the consensus is achieved among networked agents, under the constraint that each agent only knows a part of the global objective, is also worthy of further discussion and analysis. In conclusion, prescribed-time control, estimation, and optimization of networked systems are still worthy of further discussion and analysis.
The primary goal of this Research Topic is to disseminate the latest findings, new research developments, and future trends and innovations in the estimation, control, and optimization of networked systems and their applications in distributed sensor networks, electric power networks, unmanned mobile swarms, and intelligent vehicle formation and so on. Both theoretical and experimental studies are encouraged. Moreover, high-quality reviews and survey papers are welcomed.
The submitted papers may focus on, but not necessarily be limited to, the following areas:
- Robust, adaptive, and intelligent prescribed-time estimation of networked systems
- Prescribed-time safety-critical control of networked systems
- Prescribed-time resilient control of networked systems subject to various network attacks
- Prescribed-time and finite-time control of networked systems with communication delays
- Distributed control and optimization of networked systems
- Prescribed-time Nash equilibrium of games between networked systems
- Prescribed-time fault detection filtering and fault tolerant control of networked systems
- Applications in sensor networks, electric power networks, unmanned mobile swarms, and intelligent vehicle formation and so on.
However, the finite-time control, estimation, and optimization of networked systems face great challenges. On one hand, in the existing results, the finite-time zero-error convergence is dependent on the initial conditions and the exact network topology. How to achieve distributed control quickly with few constraints on the communication topologies and high accuracy is still an open problem. On the other hand, due to the large scale of networks, it is very important to estimate the state of nodes in the network effectively. Distributed state observer is widely used in a networked system to estimate the state of the tracking targets via the communication topology. It remains a big challenge to design a distributed finite-time zero-error observer on generally directed topologies, whose needed time interval is independent of the initial states of the MAS as well as network algebraic connectivity. Moreover, distributed finite-time network optimization, searching for the global optimal solution within a finite time interval while the consensus is achieved among networked agents, under the constraint that each agent only knows a part of the global objective, is also worthy of further discussion and analysis. In conclusion, prescribed-time control, estimation, and optimization of networked systems are still worthy of further discussion and analysis.
The primary goal of this Research Topic is to disseminate the latest findings, new research developments, and future trends and innovations in the estimation, control, and optimization of networked systems and their applications in distributed sensor networks, electric power networks, unmanned mobile swarms, and intelligent vehicle formation and so on. Both theoretical and experimental studies are encouraged. Moreover, high-quality reviews and survey papers are welcomed.
The submitted papers may focus on, but not necessarily be limited to, the following areas:
- Robust, adaptive, and intelligent prescribed-time estimation of networked systems
- Prescribed-time safety-critical control of networked systems
- Prescribed-time resilient control of networked systems subject to various network attacks
- Prescribed-time and finite-time control of networked systems with communication delays
- Distributed control and optimization of networked systems
- Prescribed-time Nash equilibrium of games between networked systems
- Prescribed-time fault detection filtering and fault tolerant control of networked systems
- Applications in sensor networks, electric power networks, unmanned mobile swarms, and intelligent vehicle formation and so on.
Keywords: Networked Control Systems, Prescribed-time Consensus, Distributed Estimation, Multi-Agent Systems, Distributed Optimization
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
