A hybrid model is designed by combining the genetic algorithm (GA), radial basis function neural network (RBF-NN) and Sugeno fuzzy logic to determine the optimal parameters of a proportional-integralderivative (PID) controller. Our approach used the rule base of the Sugeno fuzzy system and fuzzy PID controller of the automatic voltage regulator (AVR) to improve the system sensitive response. Th...

The concepts of the Choquet and Sugeno integrals, based on a fuzzy measure, can be adopted as useful tools in estimation of the total effectiveness of a drug when appreciating its positive influence on a collection of symptoms typical of a considered diagnosis. The expected effectiveness of the medicine is evaluated by a physician as a verbal expression for each distinct symptom. By converting ...

In this paper, a novel sliding mode control theory-based learning algorithm is proposed to train an interval type-2 fuzzy neural network using type-2 fuzzy triangular membership functions. The structure considered is a type-2 Takagi–Sugeno–Kang fuzzy logic system in which the antecedents are type-2 fuzzy sets, and consequents are crisp numbers (A2-C0). In the proposed learning algorithm, instea...

This paper describes a design problem of the controller in switched systems. A switched system is a hybrid dynamical system consisting of continuous-time subsystems and a rule that controls the switching between them. The uncertainties of stability in the switching surface is a very sufficient problem in designing a switching-type controller. The stability analysis in the switching surface and ...

This paper investigates some properties of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. First, we prove that there exists a unique solution of the T-S fuzzy Hopfield neural network. Second, we determine a condition for input-to-state stability (ISS) of the T-S fuzzy Hopfield neural network. These results will be useful to analyze dynamic behavior of fuzzy neural networks.

Recently, the study of fuzzy integral inequalities has gained much attention. The most popular method is using the Sugeno integral 1 . The study of inequalities for Sugeno integral was initiated by Román-Flores et al. 2, 3 and then followed by the others 4–11 . Now, we introduce some basic notation and properties. For details, we refer the reader to 1, 12 . Suppose that Σ is a σ-algebra of subs...

The paper presents the possibility of the design of frontal neural networks and feed-forward neural networks (without pre-processing of inputs time series) with learning algorithms on the basis genetic and eugenic algorithms and Takagi-Sugeno fuzzy inference system (with pre-processing of inputs time series) in predicting of gross domestic product development by designing a prediction models wh...

This paper tackles the problem of complexity reduction in evolving fuzzy regression models of the Takagi-Sugeno type. The incremental model adaptation process used to evolve such models over time, often produces redundancies such as overlapping rule antecedents. We propose the use of a fuzzy inclusion measure in order to detect such redundancies as well as a procedure for merging rules that are...

State estimation in nonlinear systems is important in applications like monitoring, fault diagnosis and nonlinear control. However, for large-scale systems, or naturally distributed applications, the construction and tuning of a centralized observer may present difficulties. Therefore, we propose the decomposition of the model into simpler subsystems. A large class of nonlinear systems can be w...