Application of Pattern Search Algorithm to the Non-Linear Control Allocation Problem

2008 ◽  
Author(s):  
Michael Bolender
Keyword(s):  
Search Algorithm ◽  
Pattern Search ◽  
Allocation Problem ◽  
Linear Control ◽  
Control Allocation ◽  
Pattern Search Algorithm ◽  
Non Linear

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

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2283
Author(s):  
Jairo Palacio-Morales ◽  
Andrés Tobón ◽  
Jorge Herrera
Keyword(s):  
Steady State ◽  
Fuzzy Inference ◽  
Search Algorithm ◽  
Model Identification ◽  
Pattern Search ◽  
Linear Control ◽  
Search Optimization ◽  
Non Linear ◽  
Inference Systems ◽  
Control Application

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

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