Optimization strategies for linear model predictive control

The practicality of model predictive control (MPC) is partially limited by the ability to solve optimization problems in real time. This requirement limits the viability of MPC as a control strategy for large scale processes. One strategy for improving the computational performance is to formulate MPC using a linear program. While the linear programming formulation seems appealing from a numerical standpoint, the controller does not necessarily yield good closed-loop performance. In this work, we explore MPC with an l(1) performance criterion. We demonstrate how the nonsmoothness of the objective function may yield either dead-beat or idle control performance. Copyright (C) 1998 IFAC.