scholarly journals New Advances in Distributed Control of Large-Scale Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-2 ◽  
Author(s):  
Dan Zhang ◽  
Wen-An Zhang ◽  
Zheng-Guang Wu ◽  
Kun Liu ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Distributed Control ◽  
Large Scale ◽  
Large Scale Systems

scholarly journals Adaptive Distributed Control for Large-Scale Systems with Unknown Interconnection

2020 ◽  
Vol 53 (2) ◽  
pp. 8738-8743
Author(s):  
M.F. Arevalo-Castiblanco ◽  
D. Tellez-Castro ◽  
E. Mojica-Nava ◽  
J. Sofrony
Keyword(s):  
Distributed Control ◽  
Large Scale ◽  
Large Scale Systems

Distributed control for large-scale systems with adaptive event-triggering

2016 ◽  
Vol 353 (3) ◽  
pp. 735-756 ◽  
Author(s):  
M. Guinaldo ◽  
J. Sánchez ◽  
R. Dormido ◽  
S. Dormido
Keyword(s):  
Distributed Control ◽  
Large Scale ◽  
Large Scale Systems ◽  
Event Triggering

A distributed control framework and delay-dependent stability analysis for large-scale networked control systems with non-ideal communication network

2018 ◽  
Vol 41 (3) ◽  
pp. 768-779 ◽  
Author(s):  
Ehsan Bijami ◽  
Malihe Maghfoori Farsangi
Keyword(s):  
Communication Network ◽  
Control Systems ◽  
Distributed Control ◽  
Large Scale ◽  
Large Scale Systems ◽  
Packet Dropouts ◽  
Control Scheme ◽  
Communication Links ◽  
Networked Controllers ◽  
Delay Dependent

Recently, the incorporation of telecommunication technology with control systems provides the usability of remote measurement signals for the designing of networked controllers for geographically distributed large-scale systems. However, communication network introduces new difficulties such as time delays and packet dropouts to the design of networked controllers. This paper presents a new Distributed Networked Control Scheme (DNCS) and its stability analysis for stabilizing of large-scale systems with interconnected subsystems featuring both random delays and random packet dropouts in their communication links. Firstly, a general model for large scale distributed networked system consisting of subsystems is used in which the state of each subsystem has its own time varying delay and there are also delays and packet dropouts in their interconnection communication links. To compensate the influence of subsystems on each other and enhance performance and stability margin of the closed-loop system, a suitable distributed control scheme is proposed. The stability criteria are provided based on Lyapunov-Krasovskii and Linear Matrix Inequality (LMI) techniques. For this, a new type of Lyapunov-Krasovskii functional and certain slack matrices are developed to conclude some LMI-based delay-dependent theorems for designing the control law, as well as the stabilizing of the DNCS. To evaluate the proposed method, three illustrative examples are provided. To indicate the efficiency of the suggested approach, a small-gain-based approach and an observer-based consensus method are applied for comparison. Simulation results show the effectiveness of the proposed approach to enhance the performance of large-scale networked systems among a non-ideal communication network.

scholarly journals Fast Consensus of Networked Multiagent Systems with Two-Hop Network

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Jinfeng Gao ◽  
Bin Bu ◽  
Lihui Feng ◽  
Minming Gu
Keyword(s):  
Distributed Control ◽  
Multiagent Systems ◽  
Large Scale ◽  
The State ◽  
Convergence Speed ◽  
Consensus Protocol ◽  
Large Scale Systems ◽  
Numerical Example ◽  
Communication Topology ◽  
Networked Multiagent Systems

This paper studies the consensus convergence speed of multiagent systems (MASs) from two aspects including communication topology and the state of agents. Two-hop network is considered in the communication topology. A novel consensus protocol that includes the information of the states motions and their integrals is introduced. And the protocol has much faster convergence speed by choosing some appropriate weight values. The protocol can be applied to distributed control and large-scale systems. A numerical example is presented to illustrate the effectiveness and superiority of the proposed method.

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