Abstract
This paper discusses the implementation of different nonlinear strategies in a model predictive control (MPC) framework to control an exothermic continuous stirred tank reactor. The computational efficiency of an MPC strategy depends on the method used to predict model outputs within the optimization loop. The computational requirements of collocation and numerical-based methods to solve nonlinear differential modeling equations are compared with the nonlinear quadratic dynamic matrix control (NLQDMC) formulation. The convolution coefficients for NLQDMC are obtained using analytical and numerical methods and their computational time requirements are compared.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
