This project aims to develop an analysis and control suggestion system utilizing data of PMU and WAMS to detect and control low-frequency oscillation and sub-synchronized oscillation in power system. Once oscillations are detected, a classifier is developed to identify the categories of the event. For natural oscillation, damping strategies including adjust coefficients of power system stabilizers (PSSs) is made. For forced oscillation, the system further locates the oscillation resource and determine the control strategy. Additional to conventional approaches, this project applies machine learning based methods to generate oscillation data base, identify oscillation categories, and locate the oscillation source.