The main drawback of ‘conventional’ fuzzy systems is the inability to automatically design and maintain their knowledge base. To overcome this disadvantage many types of extensions adding the adaptivity property to those systems were designed. This paper deals with the so-called direct adaptation methods of fuzzy control design and especially, with two ones of them: an improved, the so-called, self-organizing fuzzy logic controller designed by Procyk and Mamdani as well as a new hybrid adaptation structure, called gradient-incremental adaptive fuzzy controller connecting gradient-descent methods with the first type. Both types of adaptive fuzzy controllers are shown on design of an automatic pilot and control of LEGO robots. The results and comparisons to a 'conventional' (non-adaptive) fuzzy controller designed by a human operator are shown, too.
