نتایج جستجو برای: takagi sugeno t s fuzzy systems

تعداد نتایج: 2464466  

1999
Muhammad AQIL Ichiro KITA Akira YANO Soichi NISHIYAMA

An algorithm for real-time prediction of river stage dynamics using a Takagi-Sugeno fuzzy system is presented in this paper. The system is trained incrementally each time step and is used to predict onestep and multi-step ahead of river stages. The number of input variables that were considered in the analysis was determined using two statistical methods, i.e. autocorrelation and partial autoco...

2004
Huey-Jian Uang Bor-Sen Chen

In general, i t is not easy to design a decentralized controller for nonlinear interconnected systems. In this study, the stability of nonlinear interconnected systems is studied via fuzzy decentralized control method. First, the nonlinear interconnected systems are represented by an equivalent Takagi-Sugeno type fuzzy model. If the state variables are unavailable, a fuzzy observer-based state ...

2016
Dhikra Saoudi

This article is devoted to the design of a fuzzy-observer-based control for a class of nonlinear systems with bilinear terms. The class of systems considered is the Takagi-Sugeno (T-S) fuzzy bilinear model. A new procedure to design the observer-based fuzzy controller for this class of systems is proposed. The aim is to design the fuzzy controller and the fuzzy observer of the augmented system ...

Journal: :Robotics and Autonomous Systems 2003
Ahmed El Hajjaji Said Bentalba

In this paper, the path tracking (PT) control for automatic steering of vehicles is studied. The Takagi–Sugeno (T–S) fuzzy model of vehicle obtained from a nonlinear model is considered and a fuzzy controller is designed. The stability analysis is discussed using Lyapunov’s approach combined with the linear matrix inequalities (LMI) approach. Finally, simulation results are given to demonstrate...

2002
A. Ichtev J. Hellendoorn

In this paper, we address fault-tolerant control for non-linear plants. We perform soft fault detection and isolation for partial fault detection. A new method is proposed that combines model predictive controllers with fuzzy Takagi-Sugeno models. An example is presented to illustrate the functionality of the proposed approach. Keywords— Fault detection and isolation, multiple models, fuzzy Tak...

2013
Junsheng Ren Xianku Zhang

Singular system is a natural representation of dynamical systems. Guaranteed cost fuzzy control problem for a class of nonlinear singular system is addressed. The nonlinear singular system contains time-varying and norm-bounded uncertainties simultaneously in the matrices of states, delayed states and control inputs. Nonlinear singular system is formulated in the framework of Takagi-Sugeno (T-S...

Journal: :J. Applied Mathematics 2012
Yuangan Wang

Having attracted much attention in the past few years, predator-prey system provides a good mathematical model to present the correlation between predators and preys. This paper focuses on the robust stability of Lotka-Volterra predator-prey system with the fuzzy impulsive control model, and Takagi-Sugeno T-S fuzzy impulsive control model as well. Via the T-S model and the Lyapunov method, the ...

2005
VLADIMÍR OLEJ

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...

2008
Indrani Kar Laxmidhar Behera

This paper presents an elegant method for controlling nonlinear systems by modeling them in terms of a Takagi-Sugeno(T-S) fuzzy model. The concept of network inversion is used to design the controller for such a system. The proposed controller is shown to make the closed loop system stable in the sense of Lyapunov. The existing controller design techniques for T-S fuzzy model, like LMI techniqu...

2005
E. A. Al-Gallaf

This research frame work investigates the application of a clustered based Neuro-fuzzy system to nonlinear dynamic system modeling from a set of input-output training patterns. It is concentrated on the modeling via Takagi-Sugeno (T-S) modeling technique and the employment of fuzzy clustering to generate suitable initial membership functions. Hence, such created initial memberships are then emp...

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