The aim of this research is to develop a strat­ egy of reasoning under uncertainty in the context of the Fuzzy Inductive Reasoning methodology. This methodology allows the prediction of systems behavior by means of two different schemes. The first one corre­ sponds to a pattern prediction scheme, based exclusively on pattern rules. The second one corresponds to a purely Sugeno infer­ ence syste...

A simple integral Takagi-Sugeno (T-S) fuzzy control scheme suitable for many types of converters is proposed in this paper. A converter with highly nonlinear characteristics, called active high power factor correction (AHPFC), is taken as an example to show the control scheme. Indeed, we can derive a linear controller to achieve zero output regulation error for the AHPFC converter. First, we in...

In this paper a global linearization of fuzzy model is given. The parameters of global linear model are obtained by instantaneous linearization of fuzzy model. The model is given in the form of the Sugeno-Takagi fuzzy model.

This paper proposes a novel adaptive control law for nonlinear systems using Takagi-Sugeno fuzzy system. Takagi-Sugeno fuzzy system is used to identify nonlinear system components theta alpha and theta beta. Stable Indirect Adaptive control law is such that it has two control components one is certainty equivalence control and other is sliding mode control. Sliding mode controller is used to en...

The “fuzzy dot” (or fuzzy relation) representation of fuzzy rules in fuzzy rule based systems, in case of classical fuzzy reasoning methods (e.g. the Zadeh-MamdaniLarsen Compositional Rule of Inference (CRI) (Zadeh, 1973) (Mamdani, 1975) (Larsen, 1980) or the Takagi Sugeno fuzzy inference (Sugeno, 1985) (Takagi & Sugeno, 1985)), are assuming the completeness of the fuzzy rule base. If there are...

Alternative LMI Conditions for Takagi-Sugeno Systems Via Fuzzy Lyapunov Function This paper deals with the stability analysis and control design for continuous Takagi-Sugeno fuzzy systems in a linear matrix inequality (LMI) framework. New LMI stability conditions are obtained by applying a relaxation strategy in a recently proposed fuzzy Lyapunov function. In these new LMI stability conditions,...

Multimodel approaches are widely used with linear submodels, but border areas around submodels are problematic. Special cases of fuzzy linguistic equation models, which can be understood as linguistic Takagi-Sugeno (LTS) type fuzzy models, can be used to solve these problems in many cases. These models use a special nonlinear scaling approach for both inputs and outputs. The LTS models are robu...

Data privacy has become an important topic of research. Ubiquitous databases and the eclosion of web technology eases the access to information. This information can be related to individuals, and, thus, sensitive information about users can be easily accessed by interested parties. Data privacy focuses on tools and methods to protect the privacy of the respondents and data owners. In the last ...

The paper investigates a predictive control algorithm to regulate the output petroleum temperature of the tubular heat exchanger. In the controller design, a Takagi–Sugeno fuzzy model is applied in combination with the model predictive control algorithm. The process model in form of the Takagi–Sugeno fuzzy model is obtained via subtractive clustering from the plant's data set. The neural networ...

The adaptive neural fuzzy inference system is used to simulate trajectory tracking in aircraft landing operationsmanagement. The advantage of the approach is that by using the linguistic representation ability of fuzzy sets and the learning ability of neural networks, the approximate linguistic representations can be improved or updated as more data become available. This approach is illustrate...