Advanced Process Control with Applications in the Food Industry

MENG, Qingbo (2020). Advanced Process Control with Applications in the Food Industry. Doctoral, Sheffield Hallam University.

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Due to the requirements for enhanced food safety and different nutrient demand for customers, food process control is becoming an increasingly important issue in the food industry. Many advanced control methods, like adaptive control, predictive control, robust control and fuzzy logic control, have attracted increasing attention and there are many successful applications in the manufacture of dairy products in the last two decades. Applying a multi-effect falling film evaporator to remove the water from the liquid is widely used in the dairy industry. This thesis addresses some key issues concerning dairy evaporation process control which include system modelling, controller development and optimization as well as the results comparison. Fundamentally, this thesis presents a study of three effects of falling film evaporator for the milk concentration process in the dairy industry as an example. The main aim, however, is to research, develop and demonstrate different advanced control strategies, such as model predictive control (MPC) and fuzzy logic control (FLC), applied to the evaporator system for the process control purposes. They both can deal with the complex non-linear processes. But MPC can maintain the system consistency, FLC has a simple control structure and more flexiable control rules. A dynamic mathematical model of a three-effect falling film evaporator is developed by using MATLAB based on the mass and energy balance principles in this thesis for analysing the optimization and controllability of the plant. Both conventional and advanced controllers, such as conventional PID, auto-tuning PID, Model predictive control (MPC), Fuzzy logic, are described to maintain and improve the mathematical model performances. The product output concentration controlled by different strategies are obtained and compared. The results indicate that all controllers can achieve the desired targets (30%, 38% and 52% for the 1st, 2nd, and 3rd effect) within limits of acceptability, however, MPC is the most competitive advanced control strategy in this milk evaporation process.

Item Type: Thesis (Doctoral)
Thesis advisor - Zhang, Hongwei [0000-0002-7718-021X]
Thesis advisor - Halliday, Ian [0000-0003-1840-6132]
Additional Information: Director of studies: Hongwei Zhang / Thesis supervisor: Ian Halliday 'No PQ harvesting'
Research Institute, Centre or Group - Does NOT include content added after October 2018: Sheffield Hallam Doctoral Theses
Identification Number:
Depositing User: Colin Knott
Date Deposited: 03 Aug 2021 16:08
Last Modified: 03 May 2023 02:02

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