A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

In this paper, as an introduction, the nonlinear model of a distillation column is presented in order to understand the fundamental paper that the column heating actuator has in the distillation process dynamics as well as in the quality and safety of the process. In order to facilitate the implementation control strategies to maintain the heating power regulated in the distillation process, it is necessary to represent adequately the heating power actuator behavior; therefore, three different models (switching, nonlinear and fuzzy Takagi–Sugeno) of a DC-DC Buck-Boost power converter, selected to regulate the electric power regarding the heating power, are presented and compared. Considering that the online measurements of the two main variables of the converter, the inductor current and the capacitor voltage, are not always available, two different fuzzy observers (with and without sliding modes) are developed to allow monitoring the physical variables in the converter. The observers response is compared to determine which has a better performance. The role of the observer in estimating the state variables with the purpose of using them in the sensors fault diagnosis, using the analytical redundancy concept, likewise, from the estimation of these variables other non-measurable can be determined; for example, the caloric power. The stability analysis and observers gains are obtained by linear matrix inequalities (LMIs). The observers are validated by MATLAB® simulations to verify the observers convergence and analyze their response under system disturbances.

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“…n − 1. Figure 5 shows a scheme of the boiler in a distillation column, denominated plate n, its dynamics is presented in (4).…”

Section: Distillation Column Nonlinear Modelmentioning

confidence: 99%

“…In [4], the authors cope with modeling distillation columns with unknown parameters by proposing an intelligent, auto-regressive, exogenous Laguerre (AI-ARX-Laguerre) technique, which achieves average estimation accuracy improvements of 16% and 9% compared with the ARX and ARXLaguerre techniques, respectively.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Comparison of Fuzzy Models and Observers for DC-DC Converters Applied to a Distillation Column Heating Actuator

Heras-Cervantes

Téllez-Anguiano

Anzurez-Marin

et al. 2020

MCA

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“…Based on Figure 2, the proposed system modeling has three main steps: (a) ARX technique, (b) improve the robustness of the ARX technique by the orthonormal method and design of the ARX-Laguerre method, and (c) improve the accuracy of system estimation based on the fuzzy ARX-Laguerre technique. An extensive variety of sinus surgery continuum robots based on the ARX method is represented by the following equation [37]:…”

Section: Fuzzy Auto Regressive With Exogenous Input (Arx) Laguerre Symentioning

confidence: 99%

Adaptive Fuzzy-Based Fault-Tolerant Control of a Continuum Robotic System for Maxillary Sinus Surgery

Piltan

Kim

2019

Applied Sciences

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Continuum robots represent a class of highly sensitive, multiple-degrees-of-freedom robots that are biologically inspired. Because of their flexibility and accuracy, these robots can be used in maxillary sinus surgery. The design of an effective procedure with high accuracy, reliability, robust fault diagnosis, and fault-tolerant control for a surgical robot for the sinus is necessary to maintain the high performance and safety necessary for surgery on the maxillary sinus. Thus, a robust adaptive hybrid observation method using an adaptive, fuzzy auto regressive with exogenous input (ARX) Laguerre Takagi–Sugeno (T–S) fuzzy robust feedback linearization observer for a surgical robot is presented. To address the issues of system modeling, the fuzzy ARX-Laguerre technique is represented. In addition, a T–S fuzzy robust feedback linearization observer is applied to a fuzzy ARX-Laguerre to improve the accuracy of fault estimation, reliability, and robustness for the surgical robot in the presence of uncertainties. For fault-tolerant control in the presence of uncertainties and unknown conditions, an adaptive fuzzy observation-based feedback linearization technique is presented. The effectiveness of the proposed algorithm is tested with simulations. Experimental results show that the proposed method reduces the average position error from 35 mm to 2.45 mm in the presence of faults.

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Investigating Effects of Pre-Processing Variation on Time-Varying Steam Temperature of Distillation Column

Hambali

Taib

Yassin

et al. 2019

2019 IEEE 7th Conference on Systems, Process and Control (ICSPC)

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A Novel Intelligent ARX-Laguerre Distillation Column Estimation Technique

Cited by 3 publications

References 26 publications

Analysis and Comparison of Fuzzy Models and Observers for DC-DC Converters Applied to a Distillation Column Heating Actuator

Analysis and Comparison of Fuzzy Models and Observers for DC-DC Converters Applied to a Distillation Column Heating Actuator

Adaptive Fuzzy-Based Fault-Tolerant Control of a Continuum Robotic System for Maxillary Sinus Surgery

Investigating Effects of Pre-Processing Variation on Time-Varying Steam Temperature of Distillation Column

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