Online self-organizing adaptive fuzzy controller: Application to a nonlinear servo system

This paper presents a self-organizing adaptive fuzzy controller that works online. No prior knowledge about the differential equations governing the plant nor offline training is needed. Starting from very simple topologies, the algorithm uses the data obtained online during the normal operation of the system to modify the structure of the fuzzy controller. This is achieved in two phases: first, the consequents of the current fuzzy rules are adapted; in the second phase, new membership functions are added online. To show its capabilities, a real experiment with a nonlinear servo system has been carried out with satisfactory results.