A special method for system modeling is presented to develop multi-variable fuzzy models on the basis of the system’s measured input and output data. The global modeling problem is proposed to be solved in two steps: by fuzzy model configuration and fuzzy model identification. The fuzzy model configuration procedure is characterized by preliminary considerations leading to the definition of the...

a new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. we use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. then, we linearized this identified model at each sampling time to have an approximate linear time varying system. in order to stabilize...

Incipient cavitations identification is very practical and academic significance for cavity research in cooling pump of engine but it is very complicated. In this paper, a Hilbert-Huang transform(HHT) fuzzy wavelet neural network (FWNN) is proposed for incipient cavitations identification. The main incipient cavitations feature was extracted from entrance pressure fluctuation by the HHT. This F...

The inverse problem of identifying dynamic biological networks from their time-course response data set is a cornerstone of systems biology. Hill and Michaelis-Menten model, which is a forward approach, provides local kinetic information. However, repeated modifications and a large amount of experimental data are necessary for the parameter identification. S-system model, which is composed of h...

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...

the purpose of this study is identification and barrier analysis for green supply chain management implementation in sirjan's golgohar using fuzzy topsis technique and fuzzy dematel technique. at first, in this study barriers for green supply chain management are identified through literature and survey with experts and the priority processing is doing with fuzzy topsis technique. this study is...

This paper proposes a novel approach for identification of Takagi–Sugeno (T–S) fuzzy model, which is based on a new fuzzy c-regression model (FCRM) clustering algorithm. The clustering prototype in fuzzy space partition is hyper-plane, so FCRM clustering technique is more suitable to be applied in premise parameters identification of T–S fuzzy model. A new FCRM clustering algorithm (NFCRMA) is ...

This paper proposes a fuzzy modelling and identification approach oriented to the design of a PI fuzzy controller for regulating both the pitch angle and the reference torque of a wind turbine model. This strategy has been suggested for enhancing the regulator design that could represent an alternative to the standard switching controller, already implemented in the wind turbine test system. Th...

The fuzzy measure can highlight important information in analyzing component features, patterns, and trends. However, fuzzy densities and interaction effects are usually unknown or uncertain for implications thus making the fuzzy measure limited in applications. This research proposes an extended fuzzy measure to derive the conditional fuzzy densities from dominance-based rough set approach (DR...

Fuzzy rule based models have a capability to approximate any continuous function to any degree of accuracy on a compact domain. The majority of FLC design process relies on heuristic knowledge of experience operators. In order to make the design process automatic we present a genetic approach to learn fuzzy rules as well as membership function parameters. Moreover, several statistical informati...