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Consensus-Based Stability Analysis of Multi-Agent Networks
Ingyu Jang, Ethan J. LoCicero, Leila Bridgeman
The emergence of large-scale multi-agent systems has led to controller synthesis methods for sparse communication between agents. However, most sparse controller synthesis algorith…
Dissipativity-Based Distributed Stability Analysis for Networks with Heterogeneous Nonlinear Agents
Ingyu Jang, Ethan J. LoCicero, Leila Bridgeman
Stabilizing large networks of nonlinear agents is challenging; decomposition and distributed analysis of these networks are crucial for computational tractability and information s…
Issues with Input-Space Representation in Nonlinear Data-Based Dissipativity Estimation
Ethan LoCicero, Alex Penne, Leila Bridgeman
In data-based control, dissipativity can be a powerful tool for attaining stability guarantees for nonlinear systems if that dissipativity can be inferred from data. This work prov…
Dissipative Imitation Learning for Discrete Dynamic Output Feedback Control with Sparse Data Sets
Amy K. Strong, Ethan J. LoCicero, Leila J. Bridgeman
Imitation learning enables the synthesis of controllers for complex objectives and highly uncertain plant models. However, methods to provide stability guarantees to imitation lear…
Dissipative Imitation Learning for Robust Dynamic Output Feedback
Amy K. Strong, Ethan J. LoCicero, Leila Bridgeman
Robust imitation learning seeks to mimic expert controller behavior while ensuring stability, but current methods require accurate plant models. Here, robust imitation learning is…