DocumentCode
2031079
Title
Dynamic fuzzy system design for modeling and control of nonlinear dynamical processes
Author
Yilmaz, Sevcan ; Oysal, Yusuf
Author_Institution
Comput. Eng. Dept., Anadolu Univ., Eskişehir, Turkey
fYear
2015
fDate
28-30 July 2015
Firstpage
463
Lastpage
467
Abstract
This paper introduces the architecture and learning procedure of dynamic fuzzy system (DFS) and its control application with linear quadratic regulator (LQR). Our DFS model is a Takagi-Sugeno type fuzzy system. IF parts of the rules are Gaussian type membership functions and THEN parts of the rules are differential equations with linear functions of inputs. We give bioreactor modeling and control results in order to show efficiency of the proposed model.
Keywords
control system synthesis; differential equations; fuzzy control; linear quadratic control; nonlinear dynamical systems; DFS; Gaussian type membership functions; LQR; Takagi-Sugeno type fuzzy system; bioreactor control; bioreactor modeling; differential equations; dynamic fuzzy system design; linear input function; linear quadratic regulator; nonlinear dynamical process; Adaptation models; Biological system modeling; Computational modeling; Fuzzy systems; Mathematical model; Nonlinear dynamical systems; Process control; ANFIS; Dynamic Adaptive Neuro-Fuzzy Inference System; System Modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Science and Information Conference (SAI), 2015
Conference_Location
London
Type
conf
DOI
10.1109/SAI.2015.7237183
Filename
7237183
Link To Document