As is well known, the property of passivity can not only keep the stability of complex networks, but is also a nice tool for analyzing the synchronization in complex networks. Therefore, passivity theory has been extensively studied for various complex networks such as time invariant, time-varying, fuzzy, and impulsive network models. Although research on the passivity of complex networks has attracted so much attention, there are still some interesting and challenging problems deserving further investigation.

For example, most of the existing results on passivity are all based on the network models with single weight for not only the ordinary differential equation network models but also the partial differential equation network models. Practically, many real-world networks should be described by complex dynamical network models with multiweights (e.g., public traffic, roads networks, social networks, communication networks, and so on), in which the nodes are coupled by multiple coupling forms. Moreover, in many circumstances, complex networks need to achieve synchronization in finite time, thus it is necessary to establish the finite-time passivity theory for complex networks.

The objective of this Special Issue is to provide an opportunity for researchers all over the world to publish both original research and review articles with a focus on the passivity of complex networks.

Potential topics include but are not limited to the following:

• Analysis and control for passivity in complex networks with single weight
• Analysis and control for passivity in complex networks with multiweights
• Finite-time passivity in complex networks
• Analysis and control in hybrid networks
• Passivity-based cooperative control of multi-agent systems
• Finite-time passivity-based cooperative control of multi-agent systems
• Passivity-based control of mechanical systems
• Passivity-based control for electrical systems
• Passivity theory for switched systems
• Applications of passivity theory, for example, in the fields of signal processing, complexity, and fuzzy control