Over the last decade, a succession of various complex systems has emerged in the field of automatic control, following the rapid development of information and communication technologies, such as manufacturing and production systems, robotics, spacecraft, smart grids, and intelligent transportation. The development of network technology brings many challenges for the modeling, control, and optimization of today's complex systems, as well as their engineering applications. In recent years, some preliminary results have emerged on complex systems in network environments, ranging from academic research to industrial applications, including Antsaklis and Baillieul, 1 Zhang et al., 2 Zhang et al., 3 Zhu et al.,4 Hespanha et al., 5 Gupta and Chow. 6 More and more researchers are working on addressing various analysis and synthesis issues simultaneously, compensating for the deficiencies associated with this medium. Therefore, the main purpose of this special collection is to brief researchers on both the theory and practice of advances in modeling, optimization, and control for complex dynamic systems in network environments, especially on those developments that have been made in the field of engineering, and mechanical engineering in particular.This special collection consists of 12 papers, all of which cover, but are not limited to, the proposed topics and can be divided into three groups. The first group mainly focuses on the issues of modeling and simulation analysis for mechanical systems in network environments, while the second addresses the issue of advanced control in complex networked systems. Finally, the third group is concerned with stability analysis and optimization for complex networked systems.In the first group, the paper by Tian et al. 7 presents an omnidirectional mobile platform with six mecanum wheels, positing that an omnidirectional mobile platform with six mecanum wheels is more flexible and can reach the desired position more easily in narrow workspaces. The kinematic model for this platform is constructed and verified using four kinds of motion state in the simulation. The motion features of the platform corresponding to the cases of six and four wheels are discussed, and the authors demonstrate the advantages of the platform with six wheels. Moreover, thanks to