1384352

11615

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 com- putational 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 l1 performance criterion. We demonstrate how the non-smoothness of the objective function may yield either dead-beat or idle control performance.

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Model predictive control , Linear programming , optimization

Studia Iranica

289

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