This paper proposes an application of decomposed fuzzy structures for modeling and control of non-linear dynamic systems based on fuzzy relational models. The basic idea is a concept supported by the decomposition of a multivariable rule base. The set of decomposed fuzzy models based on the simplified inference break up method are proposed and applied to a dynamic systems modeling.


A comparative study of the dynamic system identification with the conventional relational model and the decomposed relational model is presented for Box-Jenkins data. A real-world example of controlling a simple magnetic suspension system — iron ball levitation control in the magnetic field of the electromagnet — demonstrates the applicability and benefits of decomposed PID-FLC.