Cooperative Tracking Control of Unknown Discrete-Time Linear Multiagent Systems Subject to Unknown External Disturbances
针对参数未知且受有界扰动的异构线性多智能体系统，提出一种分布式自适应观测器和参考模型框架，将复杂协同跟踪问题转化为参考模型对领导者的跟踪和局部鲁棒自适应控制问题，使跟踪误差收敛到残差集，无扰动时渐近收敛到零。
This article studies the tracking problem of a class of heterogeneous linear minimum-phase discrete-time multiagent systems (MASs) with unknown agent parameters in the presence of bounded disturbances. By introducing a distributed adaptive observer and a reference model, a novel framework is proposed to convert the complicated cooperative tracking problem of unknown heterogeneous MASs into a cooperative tracking problem of the reference models to the leader and a local robust model reference adaptive control problem. It is shown that under the adaptive controller designed based on the proposed framework, the tracking errors between the outputs of all the agents and the output of the leader converge to a residual set. It is also shown that the tracking errors will converge to zero asymptotically when the disturbances are absent. Compared with the existing related works, our main contribution is that the proposed framework could deal with the unknown MASs with arbitrary individual relative degrees and do not rely on any global graph information. Finally, the effectiveness of the proposed controller is illustrated by an example.