Self-organizing fuzzy controller for synchronization of two motor axes

A general method is developed to generate fuzzy control rules by self-organizing and self-learning. This method includes 3 steps: step 1 establishes the experimental system to obtain the data or describing the dynamic characteristics of the system to be considered at real time; step 2 combines the numerical information into a fuzzy rule base to describe the dynamic characteristics of the system, which emulates the operators or domain experts to obtain the linguistic representations of the system; and step 3 uses the dynamic characteristics obtained to design the fuzzy controller by the complex optimization method. The experimental results demonstrate the high performance of the proposed scheme