Log In Sign Up

Distributed optimization for a class of high-order nonlinear multi-agent systems with unknown dynamics

by   Yutao Tang, et al.

In this paper, we study a distributed optimization problem for a class of high‐order multiagent systems with unknown dynamics. In comparison with existing results for integrators or linear agents, we need to overcome the difficulties brought by the unknown nonlinearities and the optimization requirement. For this purpose, we employ an embedded control‐based design and first convert this problem into an output stabilization problem. Then, two kinds of adaptive controllers are given for these agents to drive their outputs to the global optimal solution under some mild conditions. Finally, we show that the estimated parameter vector converges to the true parameter vector under some well‐known persistence of excitation condition. The efficacy of these algorithms was verified by a simulation example.


Optimal output consensus of high-order multi-agent systems with embedded technique

In this paper, we study an optimal output consensus problem for a multia...

Multi-agent optimal consensus with unknown control directions

This letter studies the optimal consensus problem for a group of heterog...

Distributed optimal steady-state regulation for high-order multi-agent systems with external disturbances

In this paper, a distributed optimal steady-state regulation problem is ...

Optimal output consensus for nonlinear multi-agent systems with both static and dynamic uncertainties

In this technical note, we investigate an optimal output consensus probl...

A Separation-Based Methodology to Consensus Tracking of Switched High-Order Nonlinear Multi-Agent Systems

This work investigates a reduced-complexity adaptive methodology to cons...

Regularized Diffusion Adaptation via Conjugate Smoothing

The purpose of this work is to develop and study a distributed strategy ...