In this thesis , it has been tried to present a smart cyber-physical control method in order to achieve smart grid transient stability based on a multi-agent approach . Power grid is one of the key aspects of the infrastructure of a country . Therefore , any major problem in these systems can cause critical damages to other important aspects of infrastructure such as water supply network , traortation , communication , economy , etc . For this reason , smartening , optimization , and strengthening these systems against either cyberattacks or faults have attracted huge attention . On the other hand , more attention is paid to cyber-physical systems (C) in the recent years . CPS is combining computing with physical components which is made of embedded systems , computer networks , physical processes , and feedback . Usually , technologies such as internet of things (IoT) , cloud computing , big data , etc. , are utilized in C . It is expected to see a mutation in the structure of power grids which will lead to the appearance of smart grids . This change in structure will be made possible by using cyberspace and technological advances . Different approaches to control these systems in the transmission aspect are recommended . Among these , centralized and distributed approaches can be mentioned . In this thesis , we use distributed control approach on the basis of brain emotional learning . In this procedure , we control agents based on a leader-follower hierarchy . Such a control approach , not only develops a redundancy but also has an appropriate behavior in the form of transient stability when facing failures . This point is illustrated through simulation . Moreover , such an approach causes a new tendency to analyze the behavior of the system from the cyber and physical interaction point of view . Keywords : Smart grid , multi-agent system , cyber-physical system , smart learning , transient stability .
