This work integrates fundamental models and metrology sensors with state-of-the-art estimation and model-predictive control techniques in order to regulate overlay photo-lithography errors. Fundamental overlay models are presented that describe the relationship between the photo-lithography steppers and the metrology sensors. A Kalman Filter is employed that utilizes the process model and the sensor model and automatically estimates uncertain states given metrology measurements. A model-predictive controller is employed that is very effective in rejecting disturbances in the overlay process, such as tool drift and model mismatch. All overlay errors have been driven to zero +/- the measurement variance of the metrology tool. This level of control is achieved for every tool-device-layer-reticle combination.