Ottawa, ON, K1S5B6, CANADA This paper presents the implementation of recent developments in system theory within a novel framework to enhance the vibration control of helicopters. Particular focus is given to the vibration control of helicopters flying in a forward flight regime, where the system exhibits time-periodic behavior. The objective of this framework is to provide high performance controllers that can satisfy stability and design performance criteria when implemented in high-fidelity computer simulations or in real time experiments. The framework emphasizes the integration of state-of-the art coupled Computational Fluid Dynamics (CFD) /Computational Structural Dynamics (CSD) analysis in the controller design process to obtain accurate reduced-order aeroelastic models of the helicopter rotor system. Design of time-periodic H2 and H∞ controllers are proposed owing to their rigorous stability formulation based on Floquet-Lyapunov theory, and advantages over time-lifted controllers. Within this framework, the time-periodic system models in state-space form were identified using robust subspace model identification method. The time-periodic H2 and H∞ synthesis problem was solved using both Linear Matrix Inequality and periodic Riccati based formulations. The controllers performance were validated using the high-fidelity aeroelastic simulations. The computational efficiency of using these advanced methods, and the necessity of using the novel framework were demonstrated by implementing an actively controlled flap strategy for vibration suppression of helicopters. Nomenclature δ Ψ , ∆ Ψ time step of the aeroelastic model and the reduced-order model,respectively δ i trailing edge flap deflection of blade number i, positive downward λ(Ψ k ) characteristic multipliers, eigenvalues of monodromy matrix µ advance ratio Ψ τ monodromy matrix θ 0 , θ 1c , θ 1s collective and cyclic pitch A k , B k , C k , D k state-space matrices of the system at tag time k F L () lower Linear Fractional Transformation F z,i rotating frame vertical load at the root of the blade for blade number i F Z non-rotating frame vertical hub load for the rotor system k sampled tag time index in one period K k controller system model at tag time t K ∞ k and K 2 k H ∞ and H 2 Controller system model at tag time k m k number of inputs at tag time k M X non-rotating frame hub roll moment of the rotor system M y,i rotating frame blade pitch moment of blade number i M Y non-rotating frame hub pitch moment of the rotor system N period of the system in sampled-time