This paper is concerned with an uncertainty and disturbance estimator-based tracking control problem for a class of interval type-2 fractional-order Takagi-Sugeno fuzzy systems subject to time-varying delays. The footprints the underlying are taken into account capture model different levels uncertainties. estimator used promote behavior rejecting in system. First, by applying Lyapunov approach...

Uncertainty is an inherent part in controllers used for real-world applications. The use of new methods for handling incomplete information is of fundamental importance in engineering applications. We simulated the effects of uncertainty produced by the instrumentation elements in type-1 and type-2 fuzzy logic controllers to perform a comparative analysis of the systems’ response, in the presen...

This paper proposes an optimal design for interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system. In this method, the fuzzy c-means clustering algorithm is used to determine structure of fuzzy rule as well as number of rules. A hybrid between chaos firefly algorithm and genetic algorithms (CFGA) is developed, which is used to find the desirable parameters of membership functions and conseq...

Networked control systems (NCS) have been in attention for many researchers for the past ten years. Professional solutions like PROFINET or IWLAN are followed with cheaper and popular networks like ZigBee. Multiple control methodologies have been developed for this kind of systems. In this paper we threated network disadvantages as uncertainty and we reduced them with type-2 fuzzy logic control...

Full type-2 fuzzy techniques provide a more adequate representation of expert knowledge. However, such techniques also require additional computational efforts, so we should only use them if we expect a reasonable improvement in the result of the corresponding data processing. It is therefore important to come up with a practically useful criterion for deciding when we should stay with interval...

In system identification or modeling problems, interval type-2 fuzzy logic systems (IT2FLSs), which have obvious advantages for handling different sources of uncertainties, are usually constructed only using the information from sample data. This paper tries to utilize the information from both sample data and prior knowledge to design IT2FLSs to compensate the insufficiency of the information ...

The modelling of real-world complex systems is an area of ongoing interest for the research community. Real-world systems present a variety of challenges not least of which is the problem of uncertainty inherent in their operation. In this research the problem of inventory management was chosen. The goal was to discover a suitable configuration for a Simulated Annealing search with a fuzzy inve...

This paper proposes an interval type-2 Takagi-Sugeno-Kang fuzzy neural system (IT2TFNS) to develop an on-line adaptive controller using stable simultaneous perturbation stochastic approximation (SPSA) algorithm. The proposed IT2TFNS realizes an interval type-2 TSK fuzzy logic system formed by the neural network structure. Differ from the most of interval type-2 fuzzy systems, the type-reduction...

One of the advantages systems based on fuzzy logic (fuzzy systems) is possibility a soft switch from one set values input parameters system to another, when different conclusions are drawn for sets these values. A type 2 direct generalization an ordinary set. In this paper, we review some branches theory type-2 and systems. We discuss operations sets, relations, centroids describe functional re...