Predictive Functional Control Based on Fuzzy Model: Design and Stability Study
Journal of Intelligent and Robotic Systems
Fuzzy model based predictive control and comparison with other nonlinear MBPC algorithms
MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
A Decomposed-model Predictive Functional Control Approach to Air-vehicle Pitch-angle Control
Journal of Intelligent and Robotic Systems
Coprime-factorized Model Predictive Control for Unstable Processes with Delay
Journal of Intelligent and Robotic Systems
Design and Stability Analysis of Fuzzy Model-based Predictive Control—A Case Study
Journal of Intelligent and Robotic Systems
Multiple modeling and fuzzy predictive control of a tubular heat exchanger system
WSEAS Transactions on Systems and Control
Online fuzzy identification for an intelligent controller based on a simple platform
Engineering Applications of Artificial Intelligence
Self-adaptive generalized predictive control of batch reactor
MIC '07 Proceedings of the 26th IASTED International Conference on Modelling, Identification, and Control
Extension of First Order Predictive Functional Controllers to Handle Higher Order Internal Models
International Journal of Applied Mathematics and Computer Science - Special Section: Selected Topics in Biological Cybernetics, Special Editors: Andrzej Kasiński and Filip Ponulak
Control of mineral wool thickness using predictive functional control
Robotics and Computer-Integrated Manufacturing
Nonlinear uncertainty model of a magnetic suspension system
Mathematical and Computer Modelling: An International Journal
Fuzzy Control of a Helio-Crane
Journal of Intelligent and Robotic Systems
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In this paper, a new method of predictive control is presented. In this approach, a well-known method of predictive functional control is combined with fuzzy model of the process. The prediction is based on fuzzy model given in the form of Takagi-Sugeno type. The proposed fuzzy predictive control has been evaluated by implementation on heat-exchanger plant, which exhibits a strong nonlinear behavior. It has been shown that in the case of nonlinear processes, the approach using fuzzy predictive control gives very promising results. The proposed approach is potentially interesting in the case of batch reactors, heat-exchangers, furnaces, and all the processes that are difficult to model