in this paper, an intelligent controller is applied to control omni-directional robots motion. first, the dynamics of the three wheel robots, as a nonlinear plant with considerable uncertainties, is identified using an efficient algorithm of training, named lolimot. then, an intelligent controller based on brain emotional learning algorithm is applied to the identified model. this emotional lea...

This document describes the implementation of a conical tank control system using an adaptive neurofuzzy system. For implementation, indirect approach is used where controller optimized model obtained during plant identification carried out data operation. Furthermore, includes training neuro fuzzy-systems and application to tank. Regarding identification, preliminary takes place for different ...

There are many methods in identification developing every day. But identification of dynamic systems has still remained a complex open problem. One of the new effective methods of identification in nonlinear problems is identification with Neurofuzzy approach. Compared with classic neural network and wavelet network this method is faster and more accurate, demonstrated with an example in this p...

Neurofuzzy systems have been developed as grey box modelling technique ideal for the task of system identiication. Neurofuzzy models combine the mathematical structure of Associative Memory Networks (AMNs) with the transparency of fuzzy systems. This produces a modelling technique to which mathematical analysis can be applied, while being more transparent than traditional black box models. Unfo...

An online fault detection and isolation scheme for nonlinear systems based on neurofuzzy modelling and pattern matching is developed in this paper. The system is first modelled offline by a neurofuzzy network using data obtained under normal operating conditions. Another neurofuzzy network is then used to model the residual, which is the difference between the output of the system and that from...

Our original motivation for the development of the Feature Space Mapping (FSM) system came from cognitive modelling. Mind arises from complex dynamics of the brain. Approximations to this dynamics lead to a set of concepts [1] helpful in description of the mind, such as the “inner space” concept, called also the “conceptual space” or the “mind space”. Among many other aspects mind models should...

In this work the application of a neurofuzzy control system in a multimachine power system is presented. The neurofuzzy control is obtained by the off-line training of a fuzzy neural network based on

Conventional control algorithms used in pH control systems give inefficient performance, leading to use of large mixers. To improve the neutralization control process, an ANFIS based advanced controller has been proposed. In this paper, method of design of adaptive controller based on neurofuzzy technique is presented. The method uses ANFIS methodology to automatically generate fuzzy rule base ...