Graduate Research Papers

Availability

Open Access Graduate Research Paper

Abstract

Process control in industries is becoming more critical due to demands on reducing consumed energy, reducing cost, and improving system efficiency and performance. In this work, a well-developed, model-based controller is introduced and implemented in one of the most common processes in the industry. Model Predictive Controller (MPC) has been studied for ten years, but recently has emerged into small industries as the number of current applications grows. These controllers need a process model in the forms of transfer functions, step response, or state-space. Although obtaining a process model can be a cumbersome task, it is worth having it (the model includes a lot of information about the process). Regarding available resources to build a test station, complexity of the test procedure, involvement in system identification, system study, and comparison to other control algorithms, this work is the first step that must be taken. The first step is limited to a linear single input—single output system. The MPC algorithm is exploited and introduced using coding in two different environments: MATLAB and an embedded system using C code. Results of simulation and real lab measurement will be compared, and limitations and future work are also addressed.

Year of Submission

2021

Degree Name

Master of Arts

Department

Department of Technology

First Advisor

Jin Zhu

Second Advisor

Ali Kashef

Date Original

11-2021

Object Description

1 PDF file (29 pages)

Language

en

File Format

application/pdf

Share

COinS