Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice

In this paper, an approach for the tuning of a model-based non-linear predictive control (NMPC) is presented. The proposed uses pattern search optimization algorithm (PSM), which applied to pH in alkalinization process sugar juice. First, model identification made using Takagi Sugeno T-S fuzzy inference systems with multidimensional sets; next step controller parameters tuning. PSM used both cases. allows minimization uncertainty and decreases, response, error steady state when compared other authors who perform same procedure but apply algorithms. results show improvement steady-state plant response.