Control of nonlinear processes using functional expansion models |
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| Affiliation: | 1. Department of Electrical, Electronic and System Engineering, Faculty of Engineering and Built Environment, 43650 UKM, Bangi, Selangor, Malaysia;2. School of Biosciences and Biotechnology, Faculty of Science and Technology, 43650 UKM, Bangi, Selangor, Malaysia;3. Institute of Microengineering and Nanoelectrics (IMEN), 43650 UKM, Bangi, Selangor, Malaysia;4. Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, 43650 UKM, Bangi, Selangor, Malaysia;1. Centre for Energy Sciences, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. Department of Mechanical Engineering, Dhaka University of Engineering & Technology (DUET), Gazipur, 1700, Bangladesh;1. Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia;2. Department of Mechanical and Aerospace Engineering, MONASH University, Clayton Campus, Australia;3. Queensland University of Technology (QUT), Biofuel Engine Reseach Facility, Queensland, Australia;4. Mechanical Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia;1. Department of Chemistry, Faculty of Science, University of Qom, P.O. Box 37185-359, Qom, Iran;2. Center of Environmental Researches, University of Qom, Qom, Iran;3. Department of Petroleum Geoscience, Faculty of Science, Soran University, P.O. Box 624, Soran, Kurdistan Regional Government, Iraq |
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| Abstract: | Functional expansion (FEx) models are a subclass of the general block-oriented model structure for nonlinear process systems. Controller design in this context uses the internal model control (IMC) paradigm, and one can show that the resulting controllers are easily implementable. The primary advantage arises from the fact that inverting the nonlinear dynamic operator is avoided by taking advantage of the partitioned model inverse due to the special structure of FEx models. The robust stability and performance of the closed-loop system can be analyzed by expressing the FEx model as a linear uncertain system and using the structured singular value framework. We present a case study of a polymerization reactor and, for this SISO system, analyze nominal and robust stability and performance conditions as a function of the closed-loop filter constants for a given range of the input variable. |
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