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...

A Sugeno and a Choquet integrals are commonly used fuzzy integrals for aggregation. As a generalization of both integrals, the twofold integral is induced. The twofold integral enables us to interpret two measures from a different semantics viewpoint. One corresponds to the Choquet integral and the other corresponds to the Sugeno integral. Our work is about building models for the twofold integ...

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...

Introduction: In radiotherapy with external surrogates, exact information of tumor position is one of the key factors that improves treatment delivery. Many dynamic tumors in thorax region of patient move mainly due to respiration and are known as intra-fractional motion error that must be compensated, as well. One of clinical strategy is using Stereotactic Body Radiation Thera...

In this study, the road traffic congestion of Dehradun city is evaluated from traffic flow information using fuzzy techniques. Three different approaches namely Sugeno, Mamdani models which are manually tuned techniques, and an Adaptive Neuo-Fuzzy Inference System (ANFIS) which an automated model decides the ranges and parameters of the membership functions using grid partition technique, based...

Evolving fuzzy systems are data-driven fuzzy (rule-based) systems supporting an incremental model adaptation in dynamically changing environments; typically, such models are learned on a continuous stream of data in an online manner. This paper advocates the use of visualization techniques in order to help a user gain insight into the process of model evolution. More specifically, rule chains a...

A Takagi-Sugeno (T-S) fuzzy model is used to express non-linear dynamic systems with time-delay in this paper, and an on-line identi® cation algorithm is presented regarding its parameters and structures. A multivariable fuzzy generalized predictive control approach is proposed based on the identi® ed fuzzy model by means of the generalized predictive control principle. The closed-loop stabilit...

Integral inequalities play critical roles in measure theory and probability theory. Given recent profound discoveries in the field of fuzzy set theory, fuzzy inequality has become a hot research topic in recent years. For classical Sandor type inequality, this paper intends to extend the Sugeno integral. Based on the (s,m)-convex function in the second sense, a new Sandor type inequality is pro...

In this paper, the model of stochastic fuzzy Hopfield neural networks with time-varying delays and impulses (ISFVDHNNs) is established as a modified Takagi-Sugeno (TS) fuzzy model in which the consequent parts are composed of a set of stochastic Hopfield neural networks with time-varying delays and impulses. Then, the global exponential stability in the mean square for ISFVDHNNs is studied by e...