Adaptive Synchronization And Control For Complex Dynamic Networks Of Leader-following Multi-agents

In this thesis, adaptive synchronization and control for complex dynamic network ofleader-following multi-agents is investigated by using adaptive control design methods.Because network topology with different structure, the multi-agents systems withunknown nonlinear dynamics information, based on algebraic graph theory, Lyapunovstability theory, adaptive control theory, and combined with adaptive control designmethods， adaptive synchronization and control for complex dynamic network ofleader-following multi-agents can be solved via taking different network topology.We consider adaptive coordination control of multi-agents systems with switchingtopology and unknown nonlinear dynamics. According to the multi-agents system withunknown nonlinear dynamics information, based on algebraic graph theory, stabilitytheory, linear system theory, complex network dynamic theory, we design aneighbor-based state feedback control laws and adaptive control laws by using linearparametric hypothesis method. By stability analysis, parameter convergence analysis andsimulations, adaptive synchronization and control can be achieved.In view of the network topology structure with more general case, we consideradaptive synchronization and control for complex dynamic network of leader-followingmulti-agents systems. In reality, because of the requirement that the switchinginterconnected graph is connected through each time interval[t k, tk1]is a strongcondition, so we investigate the dynamic of multi-agents systems with jointly connectedtopology. By simulation results, we obtain adaptive synchronization and control.