Dynamic Fuzzy System Design for Modeling and Control of Nonlinear Dynamical Processes

Yilmaz S., Oysal Y.

Science and Information Conference (SAI), London, Canada, 28 - 30 July 2015, pp.463-467 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/sai.2015.7237183
  • City: London
  • Country: Canada
  • Page Numbers: pp.463-467
  • Keywords: ANFIS, Dynamic Adaptive Neuro-Fuzzy Inference System, System Modeling, IDENTIFICATION
  • Anadolu University Affiliated: Yes


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.