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
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;
Conference_Titel :
Science and Information Conference (SAI), 2015
Conference_Location :
London
DOI :
10.1109/SAI.2015.7237183
