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Fast Offset-Free Nonlinear Model Predictive Control Based on Moving Horizon Estimation
09 Jun 2023 | Contributor(s):: Huang, Rui, Biegler, Lorenz T., Patwardhan, Sachin C.
To deal with plant-model mismatches in control practice, this paper proposes two variations of an offset-free framework which integrates nonlinear model predictive control (NMPC) and moving horizon estimation (MHE). We prove that the proposed method achieves offset-free regulatory behavior, even...
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A Moving Horizon Estimator for processes with multi-rate measurements: A Nonlinear Programming sensitivity approach
09 Jun 2023 | Contributor(s):: Lopez-Negrete, Rodrigo, Biegler, Lorenz T.
Moving Horizon Estimation (MHE) provides a framework that allows one to incorporate both frequent and infrequent observations easily because it uses a window of past measurements, where the slower ones can be introduced as they become available. Also, MHE allows for the use of constraints on the...
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A Moving Horizon-Based Approach for Least-Squares Estimation
09 Jun 2023 | Contributor(s):: Robertson, Douglas G., Lee, Jay H., Rawlings, James B.
A general formulation of the moving horizon estimator is presented. An algorithm with a fixed-size estimation window and constraints on states, disturbances, and measurement noise is developed, and a probabilistic interpretation is given. The moving horizon formulation requires only one more...
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A comparative review of multi-rate moving horizon estimation schemes for bioprocess applications
09 Jun 2023 | Contributor(s):: Elsheikh, Mohamed, Hille, Rubin Tatulea-Codrean, Alexandru, Kramer, Stefan
Advanced control and monitoring of bioprocesses are dependent on accurate state and parameter information. At the same time, bioprocesses are well known for their time-varying behavior and difficulty of obtaining online measurements of the important process states. The selection and the tuning of...