We propose a fast real-time reinforcement learning (RL) control algorithm for large-scale
partially-observable linear dynamic systems. We first develop a one-shot RL method for …

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 …

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 …

We present a general framework for graph-based model reduction of the controlled
consensus protocol, and derive a class of edge-based graph contractions as a constructive …

This paper proposes a new analysis of graph using the concept of electric potential, and
also proposes a graph simplification method based on this analysis. Suppose that each …

Orthogonal projection-based reduced order models (PROM) are the output of widely-used
model reduction methods. In this work, a novel product form is derived for the reduction error …

This thesis considers two important problems in the theory of networked multi-agent
systems: the problem of robust consensus and synchronization and the problem of model …

Reducing a graph model is extremely important for the dynamical analysis of large-scale
networks. In order to approximate the behavior of such a system it is helpful to be able to …

In this thesis, a clustering-based method of model reduction of networked multi-agent
systems will be considered. Starting point is the method described in [3] that uses a one step …

In this paper, we study a model reduction technique for leader-follower networked multi-
agent systems defined on weighted, undirected graphs with arbitrary linear multivariable …