Abstract
AbstractConfiguration of feedback loops between input and output variables of a given plant constitutes a subtask of control system synthesis. In the past, this subtask has been tackled through direct decomposition of either the process or the set of input‐output variables. Linear interaction analysis has been used in both approaches to assess and minimize sub‐system interactions. Since most chemical processes exhibit nonlinear behavior, it is evident that a measure is needed for assessment of interactions in the presence of system nonlinearities. In this paper we focus on input‐output variable set decomposition and introduce the notion of nonlinear block relative gain (NBRG) as a nonlinear interaction measure. Both the statistic and dynamic versions of NBRG are discussed, and a computational procedure is presented for their evaluation. Direct simulations on a CSTR verify the interactions predicted by NBRG for different feedback configurations. Moreover, nonsymmetry of the effect of one loop on another, a fact not captured by the linear BRG, is accurately predicted by NBRG.
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