Characterization of driver nodes: Network of discrete-time agents
15 Jul 2015-pp 622-627
TL;DR: This work considers limited actuator amplitude of driver node and characterizes driver node based on Region of Attraction (ROA) obtained corresponding to a particular chosen driver node, to find an appropriate node such that Region ofAttraction maximizes.
Abstract: A network of discrete-time agents (nodes) which can be controlled by different nodes, acting independently, is considered When a network can be controlled through several nodes, it is important to understand differences in choosing a particular node as driver node (node which control the entire network) This work considers limited actuator amplitude of driver node and characterizes driver node based on Region of Attraction (ROA) obtained corresponding to a particular chosen driver node The presented theory and algorithms enable to find an appropriate node such that Region of Attraction maximizes Theoretical developments are verified through numerical simulation
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TL;DR: For any practical networked systems, driver node has limited actuating capacity, this paper consider this limitation a priori and presents mathematical formulation and two algorithms using the Region of Attraction (ROA) to identify an optimal set of driver nodes.
Abstract: A controllable networked system is steered from an initial state to the desired state with the help of a set of driver nodes. The set of driver nodes used to control a networked system may not be unique. There exist multiple set of driver nodes which may be utilized to control the networked system. This is imperative to characterize these sets of driver nodes for identification of an optimal set of driver nodes. This paper presents mathematical formulation and two algorithms using the Region of Attraction (ROA) to identify an optimal set of driver nodes. Optimal set of driver nodes is identified to maximize the stability region. For any practical networked systems, driver node has limited actuating capacity, this paper consider this limitation a priori. The proposed mathematical formulation and algorithms are verified with the help of numerical examples using the MATLAB simulation. The proposed algorithms have been validated by applying on a robotic network.
6 citations
17 May 2022
TL;DR: In this article , the quantized control of a complex network subject to delayed control signals is studied and the design of the control is based on the linear matrix inequalities and the descriptor approach is utilized to handle the delayed signals.
Abstract: The quantized control of a complex network subject to delayed control signals is studied. The design of the control is based on the linear matrix inequalities. Moreover, the descriptor approach is utilized to handle the delayed signals. It is shown that the system is asymptotically stabilized. Application of the descriptor approach allows to find a stabilizing control law even if the derivative of the present time delay is not bounded. Capability of handling fast time delays in combination with quantized signals makes the algorithm useful to the control of complex network through a communication network. An example illustrates the results.
01 Jan 2017
TL;DR: This paper develops an algorithm to select the optimal set of driver nodes corresponding to minimum networked sensitivity w.r.t. maximum DC-Gain and a range of frequency.
Abstract: In this paper, we investigate the correlation between optimal set of driver nodes and networked sensitivity of Complex Networked Systems (CNS). Here, we study the networked sensitivity between a pair of control and output nodes for interconnected directed and undirected networks. We investigate the importance of the optimal driver nodes based on new index of the networked control system, which is networked sensitivity in the networked system. In this paper, we discuss to select the optimal set of driver nodes corresponding to minimum networked sensitivity w.r.t. (i) maximum DC-Gain and (ii) a range of frequency. In particular, we develop an algorithm to select the optimal set of driver nodes which has minimum networked sensitivity. Finally, we validate theoretical results with the help of network examples.
17 May 2022
TL;DR: Capability of handling fast time delays in combination with quantized signals makes the algorithm useful to the control of complex network through a communication network.
Abstract: The quantized control of a complex network subject to delayed control signals is studied. The design of the control is based on the linear matrix inequalities. Moreover, the descriptor approach is utilized to handle the delayed signals. It is shown that the system is asymptotically stabilized. Application of the descriptor approach allows to find a stabilizing control law even if the derivative of the present time delay is not bounded. Capability of handling fast time delays in combination with quantized signals makes the algorithm useful to the control of complex network through a communication network. An example illustrates the results.
References
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TL;DR: This article reviews studies investigating complex brain networks in diverse experimental modalities and provides an accessible introduction to the basic principles of graph theory and highlights the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
Abstract: Recent developments in the quantitative analysis of complex networks, based largely on graph theory, have been rapidly translated to studies of brain network organization. The brain's structural and functional systems have features of complex networks--such as small-world topology, highly connected hubs and modularity--both at the whole-brain scale of human neuroimaging and at a cellular scale in non-human animals. In this article, we review studies investigating complex brain networks in diverse experimental modalities (including structural and functional MRI, diffusion tensor imaging, magnetoencephalography and electroencephalography in humans) and provide an accessible introduction to the basic principles of graph theory. We also highlight some of the technical challenges and key questions to be addressed by future developments in this rapidly moving field.
9,700 citations
TL;DR: In this article, the authors developed analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system's entire dynamics.
Abstract: The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system's entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network's degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.
2,889 citations
Book•
26 Jun 2001
TL;DR: In this article, a control system with actuator saturation analysis and design is presented, in which a control law is designed a priori to meet either the performance or stability requirement.
Abstract: From the Publisher:
"Control Systems with Actuator Saturation Analysis and Design examines the problem of actuator saturation depth. The overall approach takes into account the saturation nonlinearities at the outset of the control design. In the case that a control law is designed a priori to meet either the performance or stability requirement, it analyzes the closed loop system under actuator saturation systematically and redesigns the controller in such a way that the performance is retained while stability is improved. It also presents some related results on systems with state saturation or sensor saturation." "This book is a resource for professionals, researchers, practitioners, graduate students in control, electrical, and mechanical engineering, and all scientists and engineers interested in control systems with actuator saturation. Some first-year graduate courses in linear systems and multivariable control or some background in nonlinear control systems would greatly facilitate the reading of this book."--BOOK JACKET.
1,102 citations
TL;DR: This work shows how the symmetry structure of the network, characterized in terms of its automorphism group, directly relates to the controllability of the corresponding multi-agent system.
Abstract: In this work, we consider the controlled agreement problem for multi-agent networks, where a collection of agents take on leader roles while the remaining agents execute local, consensus-like protocols. Our aim is to identify reflections of graph-theoretic notions on system-theoretic properties of such systems. In particular, we show how the symmetry structure of the network, characterized in terms of its automorphism group, directly relates to the controllability of the corresponding multi-agent system. Moreover, we introduce network equitable partitions as a means by which such controllability characterizations can be extended to the multileader setting.
784 citations
"Characterization of driver nodes: N..." refers background in this paper
...In recent years, there have been quite a few results devoted to this problem [1]–[4], [12]–[16]....
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