MODEL PREDICTIVE CONTROL USING SEMIDEFINITE PROGRAMMING

Systems and methods include a method for optimizing an action at a facility using a prediction of a target variable. Historical data is collected for a set of facilities. The historical data includes transactional data for discrete events that occurred at the set of facilities and non-transactional data spanning continuous time periods. Semidefinite matrices are generated using the historical data, where the semidefinite matrices incorporate historical samples of a form (yt, xt, zt), and where yt is a target variable to be predicted at time t, xt is an input parameter at time t, and zt is an environment variable at time t. A statistical model based on the semidefinite matrices is determined. Production at a facility is monitored, including collecting production data comprising the transactional data and the non-transactional data of the facility. Using the statistical model and the production data, a prediction of a target variable associated with operating conditions at the facility is determined. An action at the facility is optimized using the prediction of the target variable yt.