Distributed Time-Varying Optimization for Heterogeneous Multi-Agent Systems with General Linear Dynamics

In this paper, we investigate distributed optimization problems that involve both time-varying cost functions and complex system dynamics. To address these challenges, we design a distributed control protocol with a novel class of supergradient-based distributed estimation method. Compared to existing approaches, the proposed algorithm significantly reduces storage and computational demands while maintaining the same level of convergence accuracy. Finally, we present a numerical example to demonstrate the effectiveness of the proposed control protocol.