Cooperative Adaptive Output Regulation for Lower Triangular Nonlinear Multi-Agent Systems Subject to Jointly Connected Switching Networks

• Published in: IEEE transaction on neural networks and learning systems Vol. 31; no. 5; pp. 1724 - 1734
• Main Authors: Liu, Wei, Huang, Jie
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive distributed observer; Adaptive systems; cooperative output regulation; Eigenvalues and eigenfunctions; Inverse dynamics; learning control; Lorenz system; Multi-agent systems; Multiagent systems; Networks; nonlinear multi-agent systems; Nonlinear systems; Observers; Recursive methods; Regulation; Subsystems; Switches; Switching; switching networks
• ISSN: 2162-237X; 2162-2388; 2162-2388
• DOI: 10.1109/TNNLS.2019.2922174

The cooperative global robust output regulation problem for multi-agent systems is a generalization of the leader-following consensus problem. The problem has been studied for various multi-agent systems over connected static networks and for some special classes of nonlinear multi-agent systems over jointly connected switching networks. In this paper, we further consider the same problem for a class of heterogeneous lower triangular nonlinear multi-agent systems over jointly connected switching networks. This class of systems is quite general in that it contains inverse dynamics, is of any order, and its subsystems can have different relative degrees. We will integrate the adaptive distributed observer and the distributed internal model approach to come up with a recursive approach to deal with our problem. We will also apply our approach to a leader-following consensus problem for a group of hyperchaotic Lorenz systems.