Application of Model Predictive Control algorithm on cart pole problem. MPC is the powerful technique for optimizing the performance of constrained systems. MPC uses the current plant measurements, the current dynamic state of the process, the MPC models, and the process variable targets and limits to calculate future changes in the dependent variables. These changes are calculated to hold the dependent variables close to target while honoring constraints on both independent and dependent variables. It typically sends out only the first change in each independent variable to be implemented, and repeats the calculation when the next change is required. Alternative names to this technique are dynamic matrix control, receding horizon control, dynamic linear programming, rolling horizon planning.
The full explanation is in the Report_mpc.pdf.