Multivariable additive NARX (nonlinear autoregressive with exogenous inputs) modeling of process systems is presented. The model structure is... Show moreMultivariable 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, and 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 on the basis of a simulated continuous chemical reactor that exhibits multiple steady states in the outputs for a fixed level of the input. Endnote format citation for DOI:10.1021/ie9906464 Show less
