The paper presents new Takagi-Sugeno fuzzy models for a class of plants characterized by Two Input-Single Output systems providing the fuzzy logic decision on the local model choice. In addition, it is provided a development method for controllers selected by Takagi-Sugeno-based decision rules to control these plants. The models and the development method are applied to speed control of electri...

A fuzzy observer based scheme for synchronizing two hyperchaoticoscillators via a scalar transmitted signal for cryptographic application isproposed. The Takagi-Sugeno fuzzy model exactly represents chaotic systems.Based on the general fuzzy model, the fuzzy observer of a chaotic system isdesigned on the basis of the n-shift multiple state based key encryption algorithm.The scalar transmitted s...

Takagi-Sugeno type fuzzy models are widely used for model-based control and model-based fault diagnosis. They provide high accuracy with relatively small and easy to interpret models. The problem that we address in this paper is that data driven identification of such fuzzy models is computationally costly. Whereas most identification algorithms for Takagi-Sugeno models restrict the model’s gen...

in this paper, we introduce a takagi-sugeno (ts) fuzzy model which is derived from a typical multi-layer perceptron neural network (mlp nn). at first, it is shown that the considered mlp nn can be interpreted as a variety of ts fuzzy model. it is discussed that the utilized membership function (mf) in such ts fuzzy model, despite its flexible structure, has some major restrictions. after modify...

In this paper a new Takagi–Sugeno (T–S) fuzzy model with nonlinear consequence (TSFMNC) is presented which can approximate a class of smooth nonlinear systems, nonlinear dynamical systems and nonlinear control systems. It is also proved that Takagi–Sugeno fuzzy controller with nonlinear consequence (TSFCNC) can be used to approximate a class of nonlinear state-feedback controllers using the so-...

In this paper, monitoring and sensor fault detection in a waste-water treatment process are discussed. Monitoring is based on the Takagi-Sugeno fuzzy model of a plant process obtained by using Gustafson-Kessel fuzzy clustering algorithm.The paper also explains the principle of the Takagi-Sugeno fuzzy model. The main idea is to cope with the non-linearity of a monitored process. The output of th...

This paper presents a new way to design a Fuzzy Terminal Iterative Learning Control (TILC) to control the heater temperature setpoints of a thermoforming machine. This fuzzy TILC is based on the inverse of a fuzzy model of this machine, and is built from experimental (or simulation) data with kriging interpolation. The Fuzzy Inference System usually used for a fuzzy model is the zero order Taka...

This paper investigates the identification and modeling of a greenhouse's climate using real data from greenhouse installed in LAPER laboratory Tunisia. The objective this is to propose solution problem nonlinear time-variant inputs outputs internal climate. Combining fuzzy logic technique with Least Mean Squares (LMS), robust model for temperature prediction proposed. simulation results demons...

Keywords: Fuzzy measure Sugeno integral Choquet integral Stolarsky's inequality a b s t r a c t Recently Flores-Franulič, Román-Flores and Chalco-Cano proved the Stolarsky type inequality for Sugeno integral with respect to the Lebesgue measure k. The present paper is devoted to generalize this result by relaxing some of its requirements. Moreover, Stolar-sky inequality for Choquet integral is ...

Fuzzy logic is a powerful tool to model knowledge uncertainty, measurements imprecision, and vagueness. However, there is another type of vagueness that arises when data have multiple forms of expression that fuzzy logic does not address quite well. This is the case for multiple instance learning problems (MIL). In MIL, an object is represented by a collection of instances, called a bag. A bag ...