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This paper proposes an adaptive damping controller design method by integrating online recursive closed-loop subspace model identification with model predictive control theory. The reduced order state space model which contains dominant low frequency oscillation modes was firstly identified. According to model prediction and optimization with the current state of power system as the initial state, an infinite horizon closed-loop optimal control was obtained. Online model identification and control optimization were repeated in each time interval. The strategy overcomes the inherent shortcomings of controllers with fixed parameters based on offline identification thus solves the problem of the control performance degradation due to variation of the complex operation conditions and time-varying and uncertain characteristic of system parameters. Simulation results demonstrate the effectiveness and robustness of the proposed controller in damping inter-area low frequency oscillations. The strategy to coordinate the proposed controller with PSSs and other similar controllers in multi-machine power systems is also discussed.