Linearization based on Fuzzy Rules Emulated Networks for nonaffine discrete-time systems controller

An adaptive controller for a class of unknown nonaffine discrete-time plants is introduced in this article. The proposed control law is constructed by the estimated system linearization with adjustable networks called Muti-input Fuzzy Rules Emulated Networks or MIFRENs. Only on-line learning phase, the bounded parameters inside MIFRENs and the boundary of control error are given by the proposed theorem. The validation of the main theorem is demonstrated by computer simulation system and the experimental setup for the commercial mobile robot system called Robotino (R).