A multiple linear modeling approach for nonlinear switched systems ⋆

Many applications in chemical engineering exhibit a switching character due to discrete and continuous aspects in their dynamic behavior. While first principles models of such systems can be constructed with process simulators, they are usually too complex for use in on line applications such as in model based control. The available methods for modeling of such systems mostly use linear models, such as Mixed Logic Dynamical Systems (MLD) and Piece Wise Affine (PWA) models which describe the evolution of states in each discrete mode using linear equations. Here, we present a modeling strategy for nonlinear switched systems, which is well suited for on-line applications. The method involves a trajectory based linearization and employs a model bank with a set of local linear models for each discrete operational mode. The model bank is generated by linearizing the first principles model across a carefully designed trajectory based on its capability of multi-step ahead prediction. The numerous models are clustered and representative models are selected based on the gap metric as the distance measure. The selected linear models are aggregated using Bayesian or Fuzzy approaches to obtain the global model for the nonlinear switched system. A simulation case study of spherical two tank system is presented to validate proposed modeling strategy.