Neuro-fuzzy computing, which provides efficient information processing capability by devising methodologies and algorithms for modeling uncertainty and imprecise information, forms at this juncture, a key component of soft computing. An integrated neuro-fuzzy system is simply a fuzzy inference system trained by a neural networklearning algorithm. The learning mechanism fine-tunes the underlying...

Although neuro-fuzzy models and other similar modeis have great flexibility they also have drawbacks, especially for systems which have high uncertainty associated . This paper points out which are the major drawbacks of neuro-fuzzy models and proposes a methodology to design fault detectors in uncertain systems using neuro-fuzzy models. The coolíng coil of an air-conditioning system is used as...

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function ...