Distributed Optimal Output Consensus of Uncertain Nonlinear Multi-Agent Systems over Unbalanced Directed Networks via Output Feedback

TL;DR

This paper introduces a novel observer-based output feedback control method for achieving distributed optimal output consensus in uncertain nonlinear multi-agent systems over unbalanced directed networks, relying only on agent outputs.

Contribution

It develops a two-layer controller with a decentralized output feedback scheme and high-gain observer, addressing nonlinearities and unbalanced graphs in multi-agent systems.

Findings

Semi-global convergence of agent outputs to the optimal solution.

Controller relies only on agent outputs, not states.

Applicable to nonlinear agents with Lipschitz conditions and stable zero dynamics.

Abstract

In this note, a novel observer-based output feedback control approach is proposed to address the distributed optimal output consensus problem of uncertain nonlinear multi-agent systems in the normal form over unbalanced directed graphs. The main challenges of the concerned problem lie in unbalanced directed graphs and nonlinearities of multi-agent systems with their agent states not available for feedback control. Based on a two-layer controller structure, a distributed optimal coordinator is first designed to convert the considered problem into a reference-tracking problem. Then a decentralized output feedback controller is developed to stabilize the resulting augmented system. A high-gain observer is exploited in controller design to estimate the agent states in the presence of uncertainties and disturbances so that the proposed controller relies only on agent outputs. The semi-global convergence of the agent outputs toward the optimal solution that minimizes the sum of all local cost functions is proved under standard assumptions. A key feature of the obtained results is that the nonlinear agents under consideration are only required to be locally Lipschitz and possess globally asymptotically stable and locally exponentially stable zero dynamics.