Distributed optimization for a class of high‐order nonlinear multiagent systems with unknown dynamics. (12th September 2018)

• Record Type: Journal Article
• Authors: Tang, Yutao
• Is Part Of: International journal of robust and nonlinear control. Volume 28:Number 17(2018)
• Page Start: 5545
• Page End: 5556
• Publication Date: 2018-09-12
• Subjects: adaptive control -- distributed optimization -- embedded design -- parameter convergence -- unknown dynamics; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.4330
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: 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.