Impulsive Communication With Full and Partial Information for Adaptive Tracking Consensus of Uncertain Second-Order Multiagent Systems
Yiyan Han, Zhigang Zeng · IEEE Transactions on Cybernetics · 2021
The uncertainty of dynamics is often unavoidable in practical applications especially for networked control systems while energy cost reduction is a perpetual issue for engineering. With this motivation, this article considers the adaptive tracking consensus problem of uncertain second-order multiagent systems via impulsive communication. The tracking consensus is achieved by designing proper adaptive control schemes with neural networks. Two control strategies are proposed for different cases. One considers that all state information is available while another considers only partial information can be used. Estimators equipped by followers are designed, which do not need any information about neighbors during the time interval without communication. Even though the estimators and followers are under control continuously over time, the communication among all agents is only permitted at impulsive instants. In such situations, some sufficient conditions to guarantee the estimation and convergence are obtained for both cases. It is proved that by the proposed adaptive schemes for uncertain multiagent systems, errors exist both for estimation and consensus due to uncertain dynamics and adaptive schemes. Numerical simulations, including a practical example, are presented to illustrate the effectiveness of the proposed method.