Computationally efficient optimization algorithms for model predictive control of linear systems with integer inputs

The model predictive control problem of linear systems with integer inputs results in an integer optimization problem. In case of a quadratic objective function, the optimization problem can be cast as an integer least-squares (ILS) problem. Three algorithms to solve this problem are proposed in this paper. Optimality can be traded in to reduce the computation time. An industrial case study-an inverter-driven electrical drive system-is considered to demonstrate the effectiveness of the presented techniques.