Robust Zonotopic-based Interval Fault Estimation for Multi-agent Systems with Unknown but Bounded Noise

Abstract

This paper investigates the issue of robust interval fault estimation for multi-agent systems with unknown but bounded uncertainty by zonotopic method, instead of obtaining the accurate fault estimation results by point-based strategy, this paper also achieve the estimation set containing the real augmented state that is consistent with the measurement noises and disturbances, which can provide more estimation information in practice. First, an augmented multi-agent system is obtained by treating the actuator fault as an auxiliary state vector. Then, a unified global system description is generated based on undirected graph theory and an unknown input observer is designed using the global relative output estimation error vector. Under the assumption that the uncertainties are bounded in zonotopes, the observer matrices are achieved by zonotopic method which makes the P-radius of the global augmented state estimation error zonotope is not increased. Next, the upper and lower boundaries of the augmented stated are calculated at each time instant via interval hull technique. Finally, simulation results illustrated by a multi-agent systems with four linearized model of VTOL aircraft are given.