Neuro-Fuzzy Control

Performance improvement of fuzzy logic controllers (FLC) can be achieved by adjusting the membership functions (MF). Neuro-fuzzy approaches are mostly used in such adjustment procedure, which involves several parameters of the MFs to be adjusted. In many cases, tuning the scaling factors gives the same performance as with MFs adjustment. Secondly, tuning the scaling factors is a simpler task than adjusting the membership functions. This chapter develops a mechanism of tuning the scaling factors of the PD-PI-like FLC by using a single-neuron network. Experiments show that non-linearity can be sufficiently approximated by determining the shape of the sigmoidal function.

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