Novel PCA-Based Technique for Identification of Dominant Variables for Partial Control

Abstract

The control structure problem which has been considered the central issue in modern process control has attracted large research attentions in the last three decades. There are various methods which have been developed but only a handful of them can really provide a practical solution to such an open-ended problem. The concept of partial control structure which has long been adopted in process industries has to a certain extent provided the engineers with sound theoretical foundation upon which this issue can be tackled in a systematic way. One major limitation of partial control preventing its effective adoption to solving this problem is due to its heavy reliance on engineering experiences and process knowledge in finding the dominant variables. In this paper, we propose a novel PCA-based technique to identify the dominant variables, which avoids the need for extensive experience and process knowledge. Various criteria and conditions forming the backbone of the technique are also proposed. The effectiveness of the technique is demonstrated based on its application to the continuous extractive alcoholic fermentation system.

Decentralized Control Design for Ethanol Fermentation by Zymomonas Mobilis – Multi-Scale Control Approach

“…The control of extractive alcoholic fermentation process using Baker's yeast based on the decentralized partial control strategy was studied in [10]. In the present study, the application of partial control strategy based on 3x3 extractive fermentation system using Z. mobilis is proposed.…”

Inter-Communicative Decentralized Multi-Scale Control (ICD-MSC) Scheme: A New Approach to Overcome MIMO Process Interactions

“…Note that the TSCEF system is difficult to control not only due to the severe process interactions but also because of its nonlinear dynamic behaviors [27]. A number of researchers have studied the control and optimization strategies for the alcoholic extractive fermentation process, for example, Costa et al [28] studied the control structures for the single-stage alcoholic extractive fermentation process; Sharma and Rangaiah [29] compared the performance of the three-stage fermentation integrated with pervaporation with that of the three-stage fermentation combined with extraction; they found the former to be better; Nandong et al [30] proposed a PCA-based method for the selection of control structure for the two-stage extractive fermentation process.…”

Complete Partial Control Design for Extractive Fermentation Process

“…1. Illustration of PCA-based technique for identifying the dominant variables (Nandong et al, 2010) The concept assumes that the dominant variables can be identified through the successive dataset reduction process based on the Principal Component Analysis (PCA). Fig.…”

“…It is recommended that the value of ‫ݒ‬ 80%. Significantly, the value of ߭ indicates the strength of correlation or interaction among the variables and performance measure/s in the sub-dataset involved (Nandong et al, 2010). Hence, the higher the value of ߭ the stronger is the correlation.…”

“…In this paper, a novel PCA-based technique is briefly described, which can be used as a tool to design a complete partial control strategy incorporating inventory and constraint control objectives. Note that, the detail regarding the PCAbased technique for identifying the dominant variables is available in (Nandong et al, 2010). Note that, the proposed methodology allows the engineers to design partial control without the need for extensive experience or process knowledge.…”