Adaptive Coordinated Servomechanism Problem for Networked Dynamical Systems and Its Applications

Description

Networked systems consist of a number of individuals named agents or subsystems with interactions. Compared to a single agent, a networked system is expected to work in a coordinated fashion to fulfill certain mission with greater operational flexibility and efficiency. Coordinated control problems of networked systems are motivated by fundamental applications in the real world ranging from coordination of a group of mobile robots to formation of a team of unmanned aerial vehicles. Controllers for such groups of agents are generally distributed rather than centralized. Various coordinated control problems of networked systems such as consensus, formation, and flocking have been investigated in recent years. To date, however, most of the published results are only focused on networked systems composed of simple dynamical agents modeled by single integrators, double integrators or linear systems with parameter uncertainties being zero or sufficiently small. These results are hardly applicable to real physical and social processes such as networked mobile robots with large parameter uncertainties and/or unknown external disturbances.The overall objective of this research project is to investigate the adaptive coordinated servomechanism problem for networked systems in more practical settings with less restrictive assumptions. Such a problem includes the above mentioned problems of consensus, formation and flocking as its special cases. Most distributed control algorithms for uncertain networked systems available in the literature rely on either the assumption that the parameter uncertainties are sufficiently small or the assumption that the boundaries of the parameter uncertainties are known. On the other hand, almost all the results on the coordinated servomechanism problem of networked systems assume that the dynamics of the exosystem, which generates the reference signal and/or the disturbance, are exactly known. However, neither the boundaries of the parameter uncertainties nor the exact dynamics of the exosystem in real physical and industrial systems are always available, let alone both. To address these technical challenges, a new framework and novel adaptive distributed control approaches will be developed. The theoretical results will then be applied to important engineering problems such as coordination of networked mobile robots in biomedical services and formation of a group of micro air vehicles in surveillance. The success of this project will provide answers to a number of key and fundamental issues in networked control systems, facilitate applications to a wider class of practical systems under less restrictive assumptions, and thus have the potential to impact both theoretical research and industrial applications.