This work shows an approach to achieve output consensus among heterogeneous agents in a multi-agent environment where each agent is subject to input constraints. The communication among agents is described by a time-varying directed/undirected graph. The approach is based on the well-known Internal Model Principle which uses an unstable reference system. One main contribution of this work is the characterization of the maximal constraint admissible invariant set (MCAI) for the combined agent-reference system. Typically, MCAI sets do not exist for unstable system. This work shows that for an important class of agent-reference system that is unstable, MCAI exists and can be computed. This MCAI set is used in a Reference Governor approach, combined with a projected consensus algorithm, to achieve output consensus of all agents while satisfying constraints of each. Examples are provided to illustrate the approach.

中文翻译：

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基于一类不稳定系统的约束不变集的多智能体系统共识

这项工作展示了一种在多代理环境中实现异构代理之间输出共识的方法，其中每个代理都受到输入约束。代理之间的通信由时变有向/无向图描述。该方法基于众所周知的使用不稳定参考系统的内部模型原理。这项工作的一个主要贡献是组合代理参考系统的最大约束可容许不变集 (MCAI) 的表征。通常，不稳定系统不存在 MCAI 集。这项工作表明，对于一类重要的不稳定的代理参考系统，MCAI 存在并且可以计算。该 MCAI 集用于参考调控器方法，结合投影共识算法，在满足每个代理的约束的同时实现所有代理的输出共识。提供了示例来说明该方法。