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Model-Matching type-methods and Stability of Networks consisting of non-Identical Dynamic Agents

Vlahakis, L. ORCID: 0000-0002-7039-5314 & Halikias, G. ORCID: 0000-0003-1260-1383 (2018). Model-Matching type-methods and Stability of Networks consisting of non-Identical Dynamic Agents. Paper presented at the 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems, 27-28 Aug 2018, Groningen, Netherlands. doi: 10.1016/j.ifacol.2018.12.073


Many recent approaches of distributed control over networks of dynamical agents rely on the assumption of identical agent dynamics. In this paper we propose a systematic method for removing this assumption, leading to a general approach for distributed-control stabilization of networks of non-identical dynamics. Local agents are assumed to share a minimal set of structural properties, such as input dimension, state dimension and controllability indices, which are generically satisfied for parametric families of systems. Our approach relies on the solution of certain model-matching type problems using local state-feedback and input matrix transformations which map the agent dynamics to a target system, selected to minimize the joint control effort of the local feedback-control schemes. By adapting a well-established distributed LQR control design methodology to our framework, the stabilization problem for a network of non-identical dynamical agents is solved. The applicability of our approach is illustrated via a simple UAV formation control problem.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2018 the authors. This work has been accepted to IFAC for publication under a Creative Commons Licence CC-BY-NC-ND. Final publication can be found here:
Publisher Keywords: Model-matching, distributed LQR, non-identical systems, networked control
Departments: School of Science & Technology > Engineering
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