- Conference date: 6–8 August 2012
- Location: Las Vegas, Nevada, USA
While linear model predictive control is popular since the 70s of the past century, the 90s have witnessed a steadily increasing attention from control theoretists as well as control practitioners in the area of model predictive control (MPC). The practical interest is driven by the fact that today’s processes need to be operated under tighter performance specifications. At the same time more and more constraints, stemming for example from environmental and safety considerations, need to besatisfied. Often these demands can only be met when process constraints are explicitly considered in the controller. Predictive control with constraints appears to be a well suited approach for this kind of problems. In this paper the basic principle of MPC with constraints is reviewed and some of the theoretical, computational, and implementation aspects of MPC are discussed. Furthermore the MPC with constraints was applied to linear example.
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