Optimizing pH adjustment using Smith predictor and fuzzy logic controller in CSTR

Pao Yue-kong Library Electronic Theses Database

Optimizing pH adjustment using Smith predictor and fuzzy logic controller in CSTR


Author: Ng, Chi-fai
Title: Optimizing pH adjustment using Smith predictor and fuzzy logic controller in CSTR
Degree: M.Sc.
Year: 1997
Subject: Intelligent control systems
Fuzzy systems
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Pages: 83, [8] leaves : ill. ; 31 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1403352
URI: http://theses.lib.polyu.edu.hk/handle/200/1013
Abstract: The project objective was to build a Fuzzy Logic controller, using a Smith predictor technique, to control a pH adjustment process in a continuous stirred tank reactor (CSTR) which was considered analogous to the neutralization system. As this project's concerned process is to simulate a real industrial pH adjustment system which would involve the CSTR to store water for pH adjustment, pH controller, other facilities such as chemical (acid or alkali) dosing pump(s), etc. However, so many determinands would affect the system performance such as chemical reaction at the CSTR, pH sensor sensitivity, mixing effect, process characteristics such as hydraulic retention time of the CSTR, equalization effect of influent and so on. Since pH adjustment systems are always affected by such unknown parameters of the chemical reaction and pH sensor sensitivity as well as the mixing effect in the real industrial plants, this project aims to evaluate these two conditions so as to optimize the system performance in a more economical and reliable conditions. Therefore, most of the simulated data of this project were retrieved from real plants in order to achieve the design goal. The transfer function pole and delays were determined by a time response method. The open loop system equation was found to be 16.5 * e-9s/(1+180s). As effluent from factory always has non-linear titration curve, a Fuzzy Logic controller was used to improve the system performance, while the dead time which comes from pH sensor's sensitivity during the pH adjustment would induce a time error between the sensing signal and control signal, Smith predictor is used to compensate the signals' error in the control process. However, a proportional-plus-Integral controller was also used to test the system performance and to obtain zero steady state error in order to compare with the system performance under the control condition of the Fuzzy Logic controller, and the proportional-plus-Integral controller was used in a discrete format within the digital controller. This report also discussed advantages and drawbacks of discrete time control in engineering, the relationship between the simulation plant and the real plant and the use of Smith predictor to overcome time delay problems.

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