This thesis explores cooperative control strategies for Linear Parameter-Varying (LPV) multi-agent systems. Multi-agent systems (MAS) have signicant potential in diverse applications, including electrical systems, surveillance missions, and vehicle network control. This research develops observer-based consensus control methods for LPV multi-agent systems. The primary objective is to achieve desired formations and maintain system stability. Further, the observer-based leader-following consensus control design focuses on cooperative control among agents under actuator faults. The application of Linear Matrix Inequalities (LMIs) to ensure stability across all submodels using Polya's theorem from fuzzy control theory is considered. The proposed control strategies are validated through simulations, demonstrating their ecacy in maintaining formation and achieving consensus even in the presence of faults. The main contribution of the proposed work is to develop an observer-based leader-following fault-tolerant consensus control strategy for LPV MASs. LMIs conditions are derived to ensure the existence of LPV controller, LPV observer, and LPV virtual actuator gains. While reducing conservatism, computing these gains simultaneously increases computational constraints.