Yogesh Chinnappa

Papers

Total Citations

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About

Yogesh Chinnappa’s research focuses on the control and coordination of multi-agent systems, with a particular emphasis on consensus algorithms and network dynamics. His most-cited work, “Average Consensus in Matrix-Weight-Balanced Digraphs” (2019), makes a foundational contribution by extending classical consensus theory to systems with matrix-weighted interconnections. In this paper, Chinnappa introduces the novel concept of a balanced directed graph for matrix weights, a critical step for ensuring that agents can reach an average consensus even in asymmetric, directed networks. By deriving necessary and sufficient conditions for convergence, he provides a rigorous framework that bridges graph theory and distributed control, with implications for robotics, sensor networks, and complex systems. Though his citation count is still growing—with this paper garnering 5 citations—the work is notable for its originality and technical depth, laying groundwork for future studies in heterogeneous and high-dimensional multi-agent coordination. Chinnappa’s research is particularly valuable for students and engineers seeking to understand how non-standard network topologies can be harnessed for reliable, decentralized decision-making.