Nonlinear model predictive control based on Bernstein global optimization with application to a nonlinear CSTR
2016 European Control Conference, ECC 2016
2016 European Control Conference (ECC)
MetadataShow full item record
Patil, B., Maciejowski, J., & Ling, K. (2016). Nonlinear model predictive control based on Bernstein global optimization with application to a nonlinear CSTR. 2016 European Control Conference, ECC 2016, 471-476. https://doi.org/10.1109/ECC.2016.7810329
© 2016 EUCA. We present a model predictive control based tracking problem for nonlinear systems based on global optimization. Specifically, we introduce a 'Bernstein global optimization' procedure and demonstrate its applicability to the aforementioned control problem. This Bernstein global optimization procedure is applied to predictive control of a nonlinear CSTR system. Its strength and benefits are compared with those of a sub-optimal procedure, as implemented in MATLAB using fmincon function, and two well established global optimization procedures, BARON and BMIBNB.
National Research Foundation, Singapore.
External DOI: https://doi.org/10.1109/ECC.2016.7810329
This record's URL: https://www.repository.cam.ac.uk/handle/1810/287164
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: firstname.lastname@example.org