This paper presents the development of recurrent neural network based fuzzy inference system for identification and control of dynamic nonlinear plant. The structure and algorithms of fuzzy system based on recurrent neural network are described. To train unknown parameters of the system the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are forme...

The identification of an optimized model is one of the key issues in the field of fuzzy system modeling. This has gained significant importance since; most of the real life systems are highly complex and nonlinear. Fuzzy model identification involves two stages i.e. identification of input and output membership functions as well as generation of rule base for the system being modeled. The fuzzy...

We present a fuzzy version of the Group Identification Problem ("Who is J?") introduced by Kasher and Rubinstein (1997). consider class $N = \{1,2,\ldots,n\}$ agents, each one with an opinion about membership to group J members society, consisting in function $\pi : N \to [0; 1]$, indicating for agent, including herself, degree J. problem aggregating those functions, satisfying different sets a...

In this paper, a clustering-based method is proposed for automatically constructing a multi-input TakagiSugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated by the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to prov...

The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, th...

The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, th...

Abstract Purpose of this paper: The objectives of this paper are two folds: (1) utilizing hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable RFID-based systems decision, and (2) to highlight key risks and benefits of radio frequency identification technology in healthcare industry. Design/methodology/approach: R...

FLAS (Fuzzy Linear Adaptive System) is a self-organizing fuzzy system for non-linear function identification, that uses a learning method based on clustering to generate fuzzy rules and tune their parameters. This method reduces the influence of pattern presentation order permits building prototypes with physical meaning, allows measuring the importance of each variable, and therefore reduces t...

This work presents a supervisory control strategy for Networked Control Systems. This shows the identification and control of a plant using fuzzy theory. The identification is perform through input-output data. The fuzzy model incorporates the delay dynamics within of fuzzy rules. The controller is composed by a nominal control and a proposed supervisory control from the fuzzy model. A system o...