The goal of System Identification is to obtain a reduced order model capable of reproducing the key features of the true system behavior. Some system identification methods require, as a starting point, a high order linear model of the system. Such model is then adopted as the system most reliable description and, based on it, the desired reduced order model is derived. In this scenario, one could ask "what is the best order of the high order model?". The reply to this question is not addressed in the specialized literature. This paper presents an optimization strategy that maximizes the fit index to deal with this subject.

In some system identification methods, high order ARX models are adopted as true descriptions of the process to be identified. Afterwards, such high order model is used as a basis for a model order reduction procedure. The optimization strategy for the search of the best high order (in the fit index sense) for SISO ARX models, presented in a related paper [1], is extended to the MIMO case. The analyzed system is the Wood & Berry binary distillation column [2]. In this study, the search for the best dead times associated with the high order ARX model is also addressed. The results obtained by the optimization strategy are compared with those derived by exhaustive search.

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This paper is a review of plantwide control, presenting both an introductory view for those new to the subject and also summarizing recent advances for those familiar with it. Previous reviews have been studied, summarized, and updated with new publications in the area. The major advances since the beginning of its formal studies are described, with highlighting of the most noticeable contributions. Plantwide control architectures, design techniques, and some important open research topics are addressed. Additionally, noteworthy literature and benchmarks are enumerated.

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