Fuzzy dynamic programming, fuzzy adaptive neuro control, and the general medical diagnosis problem

An indirect adaptive neuro-fuzzy speed control of induction motors

This paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. The uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. The contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

Active Suspension System Control Using Adaptive Neuro Fuzzy (ANFIS) Controller

The purpose of designing the active suspension systems is providing comfort riding and good handling in different road disturbances. In this paper a novel control method based on adaptive neuro fuzzy system in active suspension system is proposed. Choosing the proper data base to train the ANFIS has an important role in increasing the suspension system’s performance. The data base which is used...

Adaptive neuro-fuzzy wheel slip control

Due to complex and nonlinear dynamics of a braking process and complexity in the tire–road interaction, the control of automotive braking systems performance simultaneously with the wheel slip represents a challenging problem. The non-optimal wheel slip level during braking, causing inability to achieve the desired tire–road friction force strongly influences the braking distance. In addition, ...

Adaptive Neuro-Fuzzy Systems

One benefit of fuzzy systems (Zadeh, 1965; Ruspini et al., 1998; Cox, 1994) is that the rule base can be created from expert knowledge, used to specify fuzzy sets to partition all variables and a sufficient number of fuzzy rules to describe the input/output relation of the problem at hand. However, a fuzzy system that is constructed by expert knowledge alone will usually not perform as required...

Adaptive Neuro-Fuzzy Systems