Reliable predictive control with real-time applications
Model predictive control (MPC) is widely used in process industries to control constrained systems with multiple inputs and outputs. MPC is commonly used in a two-layer architecture, allowing for the upper layer to provide the optimal operating point. However, studies have shown that a significant improvement in the economic performance of the plant can be obtained if both layers are combined together. One of the issues preventing the adoption of the aforementioned control scheme is the presence of plant–model mismatch. The EU-funded ReConDa project uses the ideas that form the linear control theory to handle the structural plant–model mismatch in a robust non-linear model predictive control (NMPC) framework. As a result, a safe, reliable and resource-efficient operation is established.
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