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This paper demonstrates the application of multiple-model adaptive control (MMAC) strategy for robust damping of low-frequency electromechanical oscillation in an interconnected power system. The control algorithm uses a model-based approach to account for the variability and uncertainty involved in the postdisturbance dynamics of the system. Conventional proportional-integral-derivative (PID) controllers are tuned to achieve the desired performance for each of these models. Using a Bayesian approach, the probability of each model representing the actual power system response is computed in each iteration. The resultant control action is derived as a probability-weighted average of the individual control moves of the controllers. This strategy has been used to design and test a damping controller for a thyristor controlled series compensator (TCSC) device installed in a prototype power system. The control scheme worked satisfactorily following possible disturbances without any prior knowledge about the specific postdisturbance dynamics.