Data-Driven Cooperative Output Regulation of Linear Discrete-Time Multiagent Systems With Unknown Dynamics

This technical article conducts the research on the cooperative output regulation problem (CORP) of linear heterogeneous discrete-time multiagent systems (MASs) with the constraints of unknown dynamics. On the basis of the data-driven scheme, a state-based distributed control protocol is constructed to achieve the asymptotic tracking for leader system's reference signals while getting rid of external disturbances. Furthermore, the result is extended to the output-based case based on the least square approach. In order to cope with the unknown leader system, an observer is put forward to estimate the leader's state after obtaining the system matrices for the exosystem by utilizing the persistently exciting data. To further overcome the difficulties of the unknown dynamics of each follower, input-output relationship is constructed to infer the system matrices. Moreover, the solution to the unknown regulator equations is provided by solving the data-dependent matrix equations. Ultimately, the control gains are derived by solving the convex optimization problem. The affirmation of the whole design scheme is demonstrated by two simulation cases.