Adaptive Consensus Control for Linear Multi-Agent System with Unknown Sinusoidal Disturbances

This paper deals with consensus control for a multi-agent system, where agents are represented via state-space models. It is assumed that they are subjected to sinusoidal disturbances with unknown parameters in the input channel. The connections between the agents are represented by a cycle-free graph containing a spanning tree. An adaptive distributed control algorithm is proposed, guaranteeing asymptotic convergence of the agents' states towards consensus, provided that the agent model satisfies the controllability condition. The control algorithm consists of a distributed observer, a distributed control law, and an adaptation law. The theoretical results are proven using LaSalle's invariance principle. Finally, a simulation example is presented to demonstrate the theoretical findings. Copyright (C) 2023 The Authors.