Abstract This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education....

a reinforced concrete member in which the total span or shear span is especially small in relation to its depth is called a deep beam. in this study, a new approach based on the adaptive neural fuzzy inference system (anfis) is used to predict the shear strength of reinforced concrete (rc) deep beams. a constitutive relationship was obtained correlating the ultimate load with seven mechanical a...

toxicity of 38 aliphatic carboxylic acids was studied using non-linear quantitative structure-toxicityrelationship (qstr) models. the adaptive neuro-fuzzy inference system (anfis) was used to construct thenonlinear qstr models in all stages of study. two anfis models were developed based upon differentsubsets of descriptors. the first one used log ow k and lumo e as inputs and had good predicti...

in this paper, an optimal adaptive fuzzy integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet dc motor. in the proposed control, sliding surface of the sliding mode control is defined according to the information of position tracking error, derivatives, and error integral. in order to estimate bounds ...

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...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

An adaptive fuzzy control system with supervisory controller is proposed to improve dynamic performance of three-phase active power filter APF . The proposed adaptive fuzzy controller for APF does not build an accuratemathematical model but approximates the nonlinear characteristics of APF using fuzzy approximation. The adaptive law based on the Lyapunov analysis can adaptively adjust the fuzzy...

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...

in this paper, an observer based fuzzy adaptive controller (fac) is designed fora class of large scale systems with non-canonical non-affine nonlinear subsystems. it isassumed that functions of the subsystems and the interactions among subsystems areunknown. by constructing a new class of state observer for each follower, the proposedconsensus control method solves the problem of unmeasured sta...

in the present work, the influences of temperature, solvent concentration and ultrasonic irradiation time were numerically analyzed on viscosity reduction of residue fuel oil (rfo). ultrasonic irradiation was applied at power of 280 w and low frequency of 24 khz. the main feature of this research is prediction and optimization of the kinematic viscosity data. the measured results of eighty-four...