ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...

Numerical Control, NC, machine tool feed servo systems are time-varying, but with the poor anti-interference of conventional PID control it is difficult to achieve satisfactory setting effect. Thus this paper puts forward an online adaptive fuzzy PID setting strategy. Further, in order to improve the control performance of fuzzy PID controllers, we use a genetic algorithm to set the initial PID...

This paper proposes inverse fuzzy-model-based feed-forward fuzzy controllers to compensate non-linear terms that affect the system dynamics. The gradient-descent algorithm can be used on-line to form adaptive fuzzy controllers. This ability allows these controllers to be used in applications were the knowledge to control the process does not exist or the process is subject to changes in its dyn...

In this paper, a new architecture of fuzzy neural network (FNN) model is proposed in order to find a fuzzy solution of a fully fuzzy polynomial (FFP) with degree one. The proposed FNN is a two layer feed-forward neural network, that corresponds connection weight to output layer. The proposed architecture of artificial neural network can get a fuzzy input signal and calculates its corresponding ...

This document describes the architecture of neuro fuzzy systems. First part of the document provides a review of general notions of fuzzy logic, and structure of fuzzy systems. A procedure and different types of fuzzy reasoning are described. The second part is devoted to the neural networks and to the simplest model of artificial neuron. In the third part, the similarities and differences betw...

0957-4174/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.eswa.2008.04.001 * Corresponding author. E-mail address: [email protected] (C.H. Aladag A given observation in time series does not only depend on preceding one but also previous ones in general. Therefore, high order fuzzy time series approach might obtain better forecasts than does first order fuzzy time series approach. Definin...

This paper presents the application of an adaptive fuzzy logic controller with feed-forward component (AFLCF) to the Selective Compliance Assembly Robot Arm (SCARA Robot). The feed forward torque component is computed on-line using an artificial neural network (ANN) which has been trained off-line. This feed-forward component is designed to deliver the ideal torque component to the robot derive...

A fuzzy-logic controller (FLC) is designed to automatically adjust feed rate in order to regulate the cutting force of milling processes in a vertical machining center. The FLC has a double-loop structure, consisting of the inner PD (proportional-derivative) velocity-control loop for a feed servo and the outer fuzzylogic force-control loop. Reference cutting forces are well maintained in both n...

In this paper, we use parametric form of fuzzy number, then feed-forward neural network is presented for obtaining approximate solution for fuzzy Fredholm integro-differential equation of the second kind. This paper presents a method based on neural networks and Newton-Cotes methods with positive coefficient. The ability of neural networks in function approximation is our main objective. The pr...

The paper presents the application of a fuzzy predictive control technique to optimize the operation of a mineral grinding plant, specifically in order to maximize the ore feed rate and to follow a predetermined particle size set-point. The proposed predictive control uses linear multivariable models and a fuzzy characterization of goals and constraints to generate the appropriate values for ma...