With the introduction of new technologies in the field of command and control systems, more and more systems have been required to work, which will accelerate decisions related to command and control by establishing information flows and parallel processing. The design of such systems and their management requires organizational architecture that, in addition to changing the status quo, facilitates the adaptation of information systems to the goals of command and control. One of these complex systems is the human brain and how it is commanded and controlled in the human body, which is one of the wonders of creation. This system is the most complex network that human beings have studied in this field today. The specific integration of this network has several features that can help us in various fields in complex systems. The main reason for everyone's attention to the brain network is the strength and resilience of this network, which is the main purpose of this study. In this paper, by analyzing the brain network in both normal and patient modes, a model of this network is designed and by considering the growth algorithm and strength and resilience criteria in complex networks, a new architecture is presented to design the command and control network. In the face of a variety of attacks, localized attacks are more robust and more resilient. The designed architecture of the command and control network is measured at 5 levels. The network's special connectivity has led to strong and resilient networks.