| 1. |
- Adaldo, Antonio, 1989-, et al.
(author)
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Event-Triggered Pinning Control of Switching Networks
- 2015
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In: IEEE Transactions on Control of Network Systems. - 2325-5870. ; 2:2, s. 204-213
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Journal article (peer-reviewed)abstract
- This paper investigates event-triggered pinning control for the synchronization of complex networks of nonlinear dynamical systems. We consider networks described by time-varying weighted graphs and featuring generic linear interaction protocols. Sufficient conditions for the absence of Zeno behavior are derived and exponential convergence of a global normed error function is proven. Static networks are considered as a special case, wherein the existence of a lower bound for interevent times is also proven. Numerical examples demonstrate the effectiveness of the proposed control strategy.
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| 2. |
- Charalambous, Themistoklis, et al.
(author)
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Distributed Finite-Time Average Consensus in Digraphs in the Presence of Time Delays
- 2015
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In: IEEE Transactions on Control of Network Systems. - : IEEE. - 2325-5870. ; 2:4, s. 370-381
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Journal article (peer-reviewed)abstract
- Most algorithms for distributed averaging only guarantee asymptotic convergence. This paper introduces a distributed protocol that allows nodes to find the exact average of the initial values in a finite and minimum number of steps on interconnection topologies described by strongly connected directed graphs (digraphs). More specifically, under the assumption that each component has knowledge of the number of its outgoing links (i.e., the number of components to which it sends information), we show that the average value can be computed based on local observations over a finite time interval. The average can be obtained in a finite number of steps even when the information exchange is subject to delays. The proposed algorithm is the first in the literature that allows for distributed computation of the exact average in digraphs in finite time, with and without delays.
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| 3. |
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| 4. |
- Magnússon, Sindri, et al.
(author)
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A Distributed Approach for the Optimal Power Flow Problem Based on ADMM and Sequential Convex Approximations
- 2015
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In: IEEE Transactions on Control of Network Systems. - : IEEE Press. - 2325-5870. ; 2:3, s. 238-253
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Journal article (peer-reviewed)abstract
- The optimal power flow (OPF) problem, which playsa central role in operating electrical networks is considered. Theproblem is nonconvex and is in fact NP hard. Therefore, designingefficient algorithms of practical relevance is crucial, thoughtheir global optimality is not guaranteed. Existing semi-definiteprogramming relaxation based approaches are restricted to OPFproblems where zero duality holds. In this paper, an efficientnovel method to address the general nonconvex OPF problemis investigated. The proposed method is based on alternatingdirection method of multipliers combined with sequential convexapproximations. The global OPF problem is decomposed intosmaller problems associated to each bus of the network, thesolutions of which are coordinated via a light communicationprotocol. Therefore, the proposed method is highly scalable. Theconvergence properties of the proposed algorithm are mathematicallysubstantiated. Finally, the proposed algorithm is evaluatedon a number of test examples, where the convergence propertiesof the proposed algorithm are numerically substantiated and theperformance is compared with a global optimal method.
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| 5. |
- Magnusson, Sindri, et al.
(author)
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On the Convergence of Alternating Direction Lagrangian Methods for Nonconvex Structured Optimization Problems
- 2015
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In: IEEE Transactions on Control of Network Systems. - : IEEE Press. - 2325-5870. ; 3:3, s. 296-309
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Journal article (peer-reviewed)abstract
- Nonconvex and structured optimization problemsarise in many engineering applications that demand scalableand distributed solution methods. The study of the convergenceproperties of these methods is in general difficult due to thenonconvexity of the problem. In this paper, two distributedsolution methods that combine the fast convergence propertiesof augmented Lagrangian-based methods with the separabilityproperties of alternating optimization are investigated. The firstmethod is adapted from the classic quadratic penalty functionmethod and is called the Alternating Direction Penalty Method(ADPM). Unlike the original quadratic penalty function method,in which single-step optimizations are adopted, ADPM uses analternating optimization, which in turn makes it scalable. Thesecond method is the well-known Alternating Direction Methodof Multipliers (ADMM). It is shown that ADPM for nonconvexproblems asymptotically converges to a primal feasible pointunder mild conditions and an additional condition ensuringthat it asymptotically reaches the standard first order necessary conditions for local optimality are introduced. In thecase of the ADMM, novel sufficient conditions under whichthe algorithm asymptotically reaches the standard first ordernecessary conditions are established. Based on this, completeconvergence of ADMM for a class of low dimensional problemsare characterized. Finally, the results are illustrated by applyingADPM and ADMM to a nonconvex localization problem inwireless sensor networks.
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| 6. |
- Shi, G., et al.
(author)
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Emergent Behaviors over Signed Random Dynamical Networks : state-flipping model
- 2015
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In: IEEE Transactions on Control of Network Systems. - : IEEE. - 2325-5870. ; 2:2, s. 142-153
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Journal article (peer-reviewed)abstract
- Recent studies from social, biological, and engineering network systems have drawn attention to the dynamics over signed networks, where each link is associated with a positive/negative sign indicating trustful/mistrustful, activator/ inhibitor, or secure/malicious interactions. We study asymptotic dynamical patterns that emerge among a set of nodes that interact in a dynamically evolving signed random network. Node interactions take place at random on a sequence of deterministic signed graphs. Each node receives positive or negative recommendations from its neighbors depending on the sign of the interaction arcs, and updates its state accordingly. Recommendations along a positive arc follow the standard consensus update. As in the work by Altafini, negative recommendations use an update where the sign of the neighbor state is flipped. Nodes may weight positive and negative recommendations differently, and random processes are introduced to model the time-varying attention that nodes pay to these recommendations. Conditions for almost sure convergence and divergence of the node states are established. We show that under this so-called state-flipping model, all links contribute to a consensus of the absolute values of the nodes, even under switching sign patterns and dynamically changing environment. A no-survivor property is established, indicating that every node state diverges almost surely if the maximum network state diverges.
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| 7. |
- Tegling, Emma, et al.
(author)
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The Price of Synchrony : Evaluating the Resistive Losses in Synchronizing Power Networks
- 2015
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In: IEEE Transactions on Control of Network Systems. - : IEEE Press. - 2325-5870. ; 2:3, s. 254-266
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Journal article (peer-reviewed)abstract
- This paper investigates the resistive power losses that are incurred in keeping a network of synchronous generators in a synchronous state. These losses arise due to the transient power-flow fluctuations that occur when the system is perturbed from a synchronous state by a small transient event or in the face of persistent stochastic disturbances. We call these losses the "price of synchrony," as they reflect the real power-flow costs incurred in resynchronizing the system. In the case of small fluctuations at each generator node, we show how the total network's resistive losses can be quantified using an H-2 norm of a linear system of coupled swing equations subject to distributed disturbances. This norm is shown to be a function of transmission-line and generator properties, to scale unboundedly with network size, and to be weakly dependent on the network topology. This conclusion differentiates the price of synchrony from typical power systems stability notions, which show highly connected networks to be more coherent and, thus, easier to synchronize. In particular, the price of synchrony is more dependent on a network's size than its topology. We discuss possible implications of these results in terms of the design of future power grids, which are expected to have highly distributed generation resources leading to larger networks with the potential for greater transient losses.
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