Synchronization pertains to the property of interconnected systems according to which their dynamic behavior is coordinated in an appropriate sense. That is to say, some of their state variables, or functions of the latter for that matter, converge to each other. Synchronization may occur naturally or may be induced, controlled, and it may be present between two systems or among a large number. In the latter case, it is convenient to speak of a network of interconnected systems. Understanding synchronization, and how to control it, is an important paradigm as it is present in a variety of scenarios. These involve, e.g., networks of technological systems (robots and vehicles of different kinds), social networks (by which people exchange opinions and agree, or not), networks of biological systems (uni or pluricellular), etc. Owing to the context, the mathematical models to describe such networks and to define synchronization formally, varies dramatically. Ordinary continuous-time or discrete-time models for which modern control theory and Lyapunov stability theory are tailored result inappropriate to incorporate hybrid phenomena that intervene in the network. These may stem from sudden topology changes, the use of digital or intermittent control strategies, the presence of impacts in the intrinsic dynamics of the nodes, etc. In this invited paper, we give an overview of synchronization control problems, mostly of cooperative control of networks of autonomous vehicles (based on continuous-time models). For that matter, the first part of the paper focuses on the main contributions of [1]. Then, we give further perspectives on what we consider significant open problems on synchronization of hybrid systems and hybrid networks.

同步属于互连系统的属性，根据该属性，可以在适当的意义上协调它们的动态行为。也就是说，它们的某些状态变量或后者在此问题上的功能相互收敛。同步可以自然发生，也可以被诱导，控制，并且可能存在于两个系统之间或大量系统中。在后一种情况下，可以方便地说到互连系统的网络。理解同步以及如何控制同步是一个重要的范例，因为它存在于各种场景中。这些包括，例如，技术系统的网络（不同种类的机器人和车辆），社交网络（人们之间可以交换意见并达成共识），生物系统的网络（单细胞或多细胞）等。由于上下文的关系，描述此类网络并正式定义同步的数学模型变化很大。为其量身定制现代控制理论和Lyapunov稳定性理论的普通连续时间或离散时间模型，结果不适合将干预网络的混合现象纳入其中。这些可能是由于拓扑的突然变化，数字或间歇控制策略的使用，节点固有动态的影响等引起的。在本文中，我们概述了同步控制问题，主要是协作控制问题。自动驾驶汽车网络（基于连续时间模型）。为此，本文的第一部分集中于[1]的主要贡献。然后，