Model-matching methods and distributed control of networks consisting of a class of heterogeneous dynamic agents

Many recent results on distributed control of multi-agent networks rely on a number of simplifying assumptions that facilitate the solution of regulation problems associated with large-scale networked systems. Identical subsystem models are a typical assumption made in networked control systems which often fail in practice. In this paper, we propose a systematic method for removing this assumption, leading to a general approach to distributed-control design for stabilising networks of multiple non-identical dynamic agents. Local subsystems represented as autonomous dynamic agents are assumed to share a set of structural properties, (controllability) indices. Our approach relies on the solution of certain model-matching type problems using local state-feedback and state/input-matrix transformations that map local dynamics to a target system, selected to minimise joint control effort. By adapting well-established distributed LQR control design methodologies to our framework, the stabilisation problem of networks of non-identical dynamic agents is solved. The applicability of our approach is illustrated via a synchronisation example of eleven harmonic oscillators with non-identical dynamics communicating over a connected graph.