A Fuzzy Difference Equation Matrix Model for the Control of Multivariable Nonlinear Systems
Source abstract
Abstract
This paper proposes the Fuzzy Difference Equation Matrix Model (FDEMM), a novel predictive control algorithm designed for nonlinear multivariable systems. Standard Dynamic Matrix Control (DMC) often struggles with computational load and nonlinearities. FDEMM addresses this by integrating the Difference Equation Matrix Model (DEMM) with a generalized Takagi-Sugeno (T-S) fuzzy framework, utilizing a parameter-weighting scheme to handle overlapping membership functions. The method is validated on two distinct nonlinear systems: a binary distillation column and a delayed thermal mixing tank. Results demonstrate FDEMM’s ability to control complex systems achieving the desired output even in the presence of disturbances and noise. The proposed strategy offers a computationally efficient alternative for real-time control of complex nonlinear processes.
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Research context
OpenAlex topics: Advanced Control Systems Optimization · Advanced Control Systems Design · Process Optimization and Integration
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Affiliations
Intelligent Control Group, Centre for Automation and Robotics UPM—CSIC, Universidad Politécnica de Madrid, 28006 Madrid, Spain
Department of Electrical, Electronics, Control Engineering and Applied Physics, School of Industrial Design and Engineering, Universidad Politécnica de Madrid, 28012 Madrid, Spain
Escuela Técnica Superior de Ingenieros Industriales, Universidad Politécnica de Madrid, 28006 Madrid, Spain
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