Sampled-Data Cooperative Output Regulation: An Adaptive Distributed Continuous-Discrete Observer Approach

This article studies the sampled-data cooperative output regulation problem for linear multiagent systems. First, a novel adaptive distributed continuous-discrete observer is established to recover the leader's state, which, on one hand, only relies on the sampling output of the leader, and on the other hand, does not need to store the sampled message from neighbors. Second, by solely making use of the digital states of both the agent and the distributed observer, a certainty equivalence control law is synthesized featuring a time-varying feedforward gain. It is rigorously proven that, with this time-varying feedforward gain, the proposed control approach can achieve exponential convergence of the tracking errors given arbitrary time-varying leader's signal, and the upper bound for the sampling intervals is explicitly given. Third, for the class of chain-integrator multiagent systems, the proposed control approach does not need any restriction on the upper bound of the sampling intervals, and thus would be more practical in certain application scenarios from the perspective of energy saving. The performance of the proposed control approach is validated by the simulation results of inverter-based distributed generation systems.