Abstract
Model predictive control (MPC) refers to a class of computer control algorithms that utilize an explicit mathematical model to optimize the predicted behavior of a process. At each control interval, an MPC algorithm computes a sequence of future process adjustments that optimize a specified control objective. The first adjustment is implemented and then the calculation is repeated at the next control cycle. Originally developed to meet the particular needs of petroleum refinery and power plant control problems, MPC technology has evolved significantly in both capability and scope and can now be found in many other control application domains.
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Badgwell, T.A., Qin, S.J. (2019). Model Predictive Control in Practice. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_8-2
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DOI: https://doi.org/10.1007/978-1-4471-5102-9_8-2
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Latest
Model Predictive Control in Practice- Published:
- 14 November 2019
DOI: https://doi.org/10.1007/978-1-4471-5102-9_8-2
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Original
Model-Predictive Control in Practice- Published:
- 05 November 2014
DOI: https://doi.org/10.1007/978-1-4471-5102-9_8-1