The paper offers evolving Takagi–Sugeno (T–S) fuzzy models for a nonlinear benchmark represented by the pendulum-crane system and focused on the dynamics of pendulum angular position behavior. The rule bases and parameters of T–S fuzzy models are continuously evolved by an online identification algorithm in terms of computing the potentials of new data points. Accepting the pendulum angle as mo...

This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodolo...

The prediction of uncertain and predictive nonlinear systems is an important and challenging problem. Fuzzy logic models are often a good choice to describe such systems, however in many cases these become complex soon. commonlly, too less effort is put into descriptor selection and in the creation of suitable local rules. Moreover, in common no model reduction is applied, while this may analyz...

Abstract: This paper focuses on the Fuzzy Frequency Response: Definition and Analysis for Uncertain Dynamic Systems. In terms of transfer function, the uncertain dynamic system is partitioned into several linear sub-models and it is organized into Takagi-Sugeno (TS) fuzzy structure. The main contribution of this approach is demonstrated, from a Theorem, that fuzzy frequency response is a bounda...

This paper considers the fuzzy modeling and robust fuzzy variable control for quadrotor in uncertain environment. The nonlinear system of quadrotor is firstly analyzed in this paper by utilizing laws of motion and force. Then, a Takagi-Sugeno (T-S) fuzzy model is achieved to approximate the system. LMI method is used to acquire an improved sliding surface. On this basis, a fuzzy variable struct...

This paper presents a robust indirect model reference fuzzy control scheme for control and synchronization of chaotic nonlinear systems subject to uncertainties and external disturbances. The chaotic system with disturbance is modeled as a Takagi–Sugeno fuzzy system. Using a Lyapunov function, stable adaptation laws for the estimation of the parameters of the Takagi–Sugeno fuzzy model are deriv...

A type of flexible models in the form of a neural network (NN) with evolving structure is treated in the paper. We refer to models with amorphous structure as flexible models. There is a close link between different types of flexible models: fuzzy models, fuzzy NN, and general regression model. All of them are proven universal approximators and some of them (Takagi-Sugeno fuzzy model with singl...

The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzz...

This work presents a method to incorporate standard neuro-fuzzy learning for Takagi–Sugeno fuzzy systems that evolve under a grammar driven genetic programming (GP) framework. This is made possible by introducing heteroglossia in the functional GP nodes, enabling them to switch behavior according to the selected learning stage. A context-free grammar supports the expression of arbitrarily sized...

In this paper, we review two of the most well-known citation indexes and establish their connections with the Choquet and Sugeno integrals. In particular, we show that the recently established -index is a particular case of the Sugeno integral, and that the number of citations corresponds to the Choquet integral. In both cases, they use the same fuzzy measure. The results presented here permit ...