Asynchronous H ∞ consensus control for singular Markov jump multi-agent systems under a sample-data-based distributed dynamic event-triggered scheme

This paper introduces a novel approach leveraging a sample -data -based, distributed, dynamic event -triggered framework to develop an H infinity asynchronous consensus controller tailored for singular Markov jump multi -agent systems (MJMASs). This approach primarily focuses on mitigating the communication load inherent in singular multi -agent systems. We employ a hidden Markov model (HMM) to adeptly manage the mode synchronization discrepancies between the controller and the system. We establish the stochastic admissibility with H infinity consensus performance of the singular consensus error system by deriving linear matrix inequalities (LMIs). Furthermore, we introduce a co -design methodology for optimizing controller gains, which simultaneously addresses the requirements of H infinity consensus and the dynamic event -triggered framework. The effectiveness of our proposed method are demonstrated through three numerical examples, each employing a different triggering mechanism.