This paper presents an application of adaptive neuro-fuzzy (ANFIS) control for switched reluctance motor (SRM) speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed cont...

The Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference System (FIS) has attracted a growing interest of researchers in various scientific and engineering areas due to the growing need for adaptive intelligent systems to solve real world problems. ANN learns by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of fuzzy set theory...

Fuzzy logic is a powerful tool to model knowledge uncertainty, measurements imprecision, and vagueness. However, there is another type of vagueness that arises when data have multiple forms of expression that fuzzy logic does not address quite well. This is the case for multiple instance learning problems (MIL). In MIL, an object is represented by a collection of instances, called a bag. A bag ...

This paper illustrates a Comparative study of highly non-linear, complex and multivariable Inverted Pendulum (IP) system on Cart using different soft computing techniques. Firstly, a Fuzzy logic controller was designed using triangular and trapezoidal shape Membership functions (MF's). The trapezoidal fuzzy controller shows better results in comparison to triangular fuzzy controller. Secondly, ...

This chapter discusses the foundation of neuro-fuzzy systems. First, we introduce Takagi, Sugeno, and Kang (TSK) fuzzy model [l,2] and its difference from the Mamdani model. Under the idea of TSK fuzzy model, we discuss a neuro-fuzzy system architecture: Adaptive Network-based Fuzzy Inference System (ANFIS) that is developed by Jang [3]. This model allows the fuzzy systems to learn the paramete...

introduction: epilepsy is a clinical syndrome in which seizures have a tendency to recur. sodium valproate is the most effective drug in the treatment of all types of generalized seizures. finding the optimal dosage (the lowest effective dose) of sodium valproate is a real challenge to all neurologists. in this study, a new approach based on adaptive neuro-fuzzy inference system (anfis) was pre...

the uv-spectrophotometric method of analysis was proposed for simultaneous determination of fluoxetine (flx) and sertraline (srt). considering the strong spectral overlap between uv-vis spectra of these compounds, a previous separation should be carried out in order to determine them by conventional spectrophotometric techniques. here, full-spectrum multivariate calibrations adaptive neuro-fuzz...

For double inverted pendulum multivariable, strong coupling and nonlinear proposed adaptive fuzzy neural inference system (ANFIS) is applied inverted pendulum stabilization control process. Adaptive control algorithm, fully able to meet the requirements of double inverted pendulum control, ANFIS system after training, will be applied to the inverted pendulum system controller has better control...

This paper proposes an ANFIS (Adaptive Network Based Fuzzy Inference System) Learning Approach where we have found patterns of personality types using Big Five Personality Tests for Software Engineering Roles in Software Development Project Teams as part of RAMSET (Role Assignment Methodology for Software Engineering Teams) methodology. An ANFIS model is applied to a set of role traits resultin...

This study deals with the design of distributed power systems and optimal capacitor placement based on the ANFIS (Adaptive Network Fuzzy Inference Systems) using Mamdani-type fuzzy inference model. Traditionally, this problem of optimal capacitor placement has been solved through various optimization techniques, but it is less accuracy of finding placement and more time consuming. This can be a...