Title: Distributed Coordination for a Class of Nonlinear Multi-agent Systems with Regulation Constraints,
Abstract: In this paper, a multi-agent coordination problem with steady-state
regulation constraints is investigated for a class of nonlinear systems. Unlike
existing leader-following coordination formulations, the reference signal is
not given by a dynamic autonomous leader but determined as the optimal solution
of a distributed optimization problem. Furthermore, we consider a global
constraint having noisy data observations for the optimization problem, which
implies that reference signal is not trivially available with existing
optimization algorithms. To handle those challenges, we present a
passivity-based analysis and design approach by using only local objective
function, local data observation and exchanged information from their
neighbors. The proposed distributed algorithms are shown to achieve the optimal
steady-state regulation by rejecting the unknown observation disturbances for
passive nonlinear agents, which are persuasive in various practical problems.
Applications and simulation examples are then given to verify the effectiveness
of our design.