Advantages of an easy to design fuzzy predictive algorithm in control systems of nonlinear chemical reactors |
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| Authors: | Piotr M Marusak |
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| Affiliation: | 1. Department of Internal Medicine, LAC + USC Medical Center, Los Angeles, California;2. Non-Invasive Diagnostic Services and Echocardiography Laboratories, Keck School of Medicine, University of Southern California, Los Angeles, California;3. Echocardiography Laboratory, Mayo Clinic, Scottsdale, Arizona;1. College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, PR China;2. Department of Information Technology, Hunan Women''s University, Changsha, Hunan 410004, PR China |
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| Abstract: | Advantages of a fuzzy predictive control algorithm are discussed in the paper. The fuzzy predictive algorithm is a combination of a DMC (Dynamic Matrix Control) algorithm and Takagi–Sugeno fuzzy modeling, thus it inherits advantages of both techniques. The algorithm is numerically effective. It is in fact generalization of the standard DMC algorithm widely used in the industry, thus the existing implementations of the DMC algorithm can be extended using the presented fuzzy approach. A simple and easy to apply method of fuzzy predictive control algorithms synthesis is presented in the paper. It can be easy applied also in the case of Multiple Input Multiple Output (MIMO) control plants. Moreover, information about measured disturbance can be included in the algorithms in an easy way. The advantages of the fuzzy predictive control algorithm are demonstrated in the example control systems of two nonlinear chemical reactors: the first one—with inverse response and the second one—a MIMO plant with time delay. |
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