Communication-Aware Dissipative Control for Networks of Heterogeneous Nonlinear Agents

Communication-aware control is essential to reduce costs and complexity in large-scale networks. However, it is challenging to simultaneously determine a sparse communication topology and achieve high performance and robustness. This work achieves all three objectives through dissipativity-based, sparsity-promoting controller synthesis. The approach identifies an optimal sparse structure using either weighted l1 penalties or alternating direction methods of multipliers (ADMM) with a cardinality term, and iteratively solves a convexified version of the NP hard structured optimal control problem. The proposed methods are demonstrated on heterogeneous networks with uncertain and unstable agents.