Abstract
Abstract Multivariable additive NARX (Nonlinear Autoregressive with eXogenous inputs) modeling of process systems is presented. The model structure is similar to that of a Generalized Additive Model (GAM) and is estimated with a nonlinear Canonical Variate Analysis (CVA) algorithm called CANALS. The system is modeled by partitioning the data into two groups of variables. The first is a collection of future outputs, the second is a collection of past input and outputs, and future inputs. This approach is similar to linear subspace state space modeling. An illustrative example of modeling is presented based on a simulated continuous stirred tank reactor that exhibits multiple steady states in the outputs.
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.
