Hidde-Jan Jongsma

Robust synchronization of coprime factor perturbed networks

This paper deals with robust synchronization of directed and undirected multi-agent networks with uncertain agent dynamics. Given a network with identical nominal dynamics, we allow uncertainty in the form of coprime factor perturbations of the transfer matrix of the agent dynamics. These perturbations are assumed to be stable and have H-infinity-norm that is bounded by an a priori given desired tolerance. We derive state space equations for dynamic observer based protocols that achieve robust synchronization in the presence of such uncertainty. We obtain an achievable interval, i.e. an interval such that for each value of the tolerance contained in this interval there exists a robustly synchronizing protocol

Model reduction of linear multi-agent systems by clustering with \(\varvec{\mathcal {H}_2}\) and \(\varvec{\mathcal {H}_\infty }\) error bounds

In the recent paper (Monshizadeh et al. in IEEE Trans Control Netw Syst 1(2):145–154, 2014. https://doi.org/10.1109/TCNS.2014.2311883), model reduction of leader–follower multi-agent networks by clustering was studied. For such multiagent networks, a reduced order network is obtained by partitioning the set of nodes in the graph into disjoint sets, called clusters, and associating with each cluster a single, new, node in a reduced network graph. In Monshizadeh et al. (2014), this method was studied for the special case that the agents have single integrator dynamics. For a special class of graph partitions, called almost equitable partitions, an explicit formula was derived for the H2 model reduction error. In the present paper, we will extend and generalize the results from Monshizadeh et al. (2014) in a number of directions. This research is supported by a research grant of the “International Max Planck Research School (IMPRS) for Advanced Methods in Process and System Engineering (Magdeburg)”. B Petar Mlinarić mlinaric@mpi-magdeburg.mpg.de Hidde-Jan Jongsma h.jongsma@rug.nl Sara Grundel grundel@mpi-magdeburg.mpg.de Peter Benner benner@mpi-magdeburg.mpg.de Harry L. Trentelman h.l.trentelman@rug.nl 1 Johann Bernoulli Institute for Mathematics and Computer Science, University of Groningen, Groningen, The Netherlands 2 Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany

Model reduction of networked multi-agent systems by cycle removal

In this paper, we consider the problem of model reduction of consensus networks. We propose a new method of model reduction based on removing edges that close cycles in the network graph. The agent dynamics of the consensus network is given by a symmetric multivariable input-state-output system. In the network, the agents exchange relative output information with their neighbors. We assume that the network graph is connected, unweighted, and undirected. The network used to approximate the original system is defined on the same number of nodes as the original graph, but its edge set is a strict subset of the original edge set. Explicit expressions and upper bounds for the approximation errors are formulated in terms of the signed path vectors of the removed edges and the eigenvalues of the Laplacian matrices of the original and reduced network graphs.

Model reduction of consensus networks by graph simplification

In this paper we consider the problem of approximating a consensus network by a less complex network, by removing cycles from the original network graph. The consensus network consists of agents that exchange relative state information with their neighbors in the network. We assume the agents have single-integrator dynamics and the network graph is undirected. The network used to approximate the original system has the same nodes as the original graph, but its edge set is a strict subset of the original edge set. We obtain a priori upper bounds on the absolute approximation error, depending on the length of the removed cycles, the algebraic connectivity of a chosen spanning tree of the network graph, and the largest eigenvalue of the Laplacian matrix of that spanning tree.

Robust synchronization of coprime factor perturbed multi-agent systems

This paper deals with robust synchronization of undirected multi-agent networks with uncertain agent dynamics. Given an undirected network with identical nominal dynamics for each agent, we allow uncertainty in the form of coprime factor perturbations of the transfer matrix of the agent dynamics. We assume that these perturbations are stable and have H∞-norm that is bounded by some a priori given desired tolerance. In this paper, we derive state space equations for dynamic observer based protocols that achieve synchronization in the presence of such perturbations. We show that this robust synchronization of the network by the dynamic protocol is equivalent to robust stabilization of a single linear system by all controllers from a related finite set of feedback controllers. Our protocols are expressed in terms of real symmetric solutions to certain algebraic Riccati equations, and contain weighting factors depending on the eigenvalues of the graph Laplacian. We show that in this class of dynamic protocols, one can achieve a guaranteed tolerance that is proportional to the square root of the quotient of the smallest and the largest eigenvalue of the graph Laplacian.