Abstract
In this paper, a fully distributed output regulation problem is investigated for a linear multi-agent system with both cooperative and competitive interactions. The interaction network associated with the multi-agent system is conveniently modeled by an undirected signed graph and called coopetition network for simplicity. In most literatures on cooperative output regulation problems, it is commonly assumed that the state matrix of the exogenous system is available to all agents. In this paper, a distributed adaptive observer is developed for each agent to estimate the state and the state matrix of the exogenous system to relax the constraint. Furthermore, a reduced-order observer based controller is proposed for each agent by using an internal model approach to guarantee bipartite consensus. Finally, simulation results are provided to demonstrate the proposed control strategy.
Original language | English |
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Pages (from-to) | 178-187 |
Number of pages | 10 |
Journal | Neurocomputing |
Volume | 281 |
DOIs | |
State | Published - Mar 15 2018 |
Keywords
- Bipartite consensus
- Coopetition network
- Distributed output regulation
- Internal model
- Reduced-order observer