Avoiding Unmeasured Premise Variables in Designing Unknown Input Observers for Takagi–Sugeno Fuzzy Systems

This paper deals with the synthesis of a new fuzzy controller applied to Electronic Throttle Valve (ETV) affected by an unknown input in order to enhance the rapidity and accuracy of trajectory tracking performance. Firstly, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate this nonlinear system. Secondly, a novel Nonlinear Unknown Input Observer (NUIO)-based controller is designed by the use of the concept of Parallel Distributed Compensation (PDC). Then, based on Lyapunov method, asymptotic stability conditions of the error dynamics are given by solving Linear Matrix Inequalities (LMIs). Finally, the effectiveness of the proposed control strategy in terms of tracking trajectory and in the presence of perturbations is verified in comparison with a control strategy based on Unknown Input Observers (UIO) of the ETV described by a switched system for Pulse-Width-Modulated (PWM) reference signal.

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Relaxed design conditions for Takagi-Sugeno unknown input observers

2017 IEEE 15th International Symposium on Applied Machine Intelligence and Informatics (SAMI) ◽

10.1109/sami.2017.7880276 ◽

2017 ◽

Cited By ~ 1

Author(s):

Dusan Krokavec ◽

Anna Filasova

Keyword(s):

Unknown Input ◽

Unknown Input Observers ◽

Takagi Sugeno

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State and unknown input estimation using proportional multiple integral observer for uncertain Takagi-Sugeno fuzzy systems

2017 International Conference on Control, Automation and Diagnosis (ICCAD) ◽

10.1109/cadiag.2017.8075629 ◽

2017 ◽

Author(s):

Ilyes Elleuch ◽

Atef Khedher ◽

Kamel Ben Othmen

Keyword(s):

Fuzzy Systems ◽

Multiple Integral ◽

Unknown Input ◽

Input Estimation ◽

Unknown Input Estimation ◽

Takagi Sugeno

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H∞ control for Takagi–Sugeno fuzzy systems

International Journal of Systems Science ◽

10.1080/00207720010004430 ◽

2001 ◽

Vol 32 (7) ◽

pp. 915-924 ◽

Cited By ~ 9

Author(s):

Jun Yoneyama ◽

Masahiro Nishikawa ◽

Hitoshi Katayama ◽

Akira Ichikawa

Keyword(s):

Fuzzy Systems ◽

Takagi Sugeno

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Modeling of Self-Induced Vibrations that Occur During the Machining Process of Casting Patterns with the Use of The Fuzzy-Neural Networks Method

Archives of Metallurgy and Materials ◽

10.2478/amm-2013-0090 ◽

2013 ◽

Vol 58 (3) ◽

pp. 871-875

Author(s):

A. Herberg

Keyword(s):

Neural Networks ◽

Control System ◽

Network Structure ◽

Fuzzy Systems ◽

Fuzzy Neural Networks ◽

Cnc Machining ◽

Machining Process ◽

Modeling Process ◽

Fuzzy Neural ◽

Takagi Sugeno

Abstract This article outlines a methodology of modeling self-induced vibrations that occur in the course of machining of metal objects, i.e. when shaping casting patterns on CNC machining centers. The modeling process presented here is based on an algorithm that makes use of local model fuzzy-neural networks. The algorithm falls back on the advantages of fuzzy systems with Takagi-Sugeno-Kanga (TSK) consequences and neural networks with auxiliary modules that help optimize and shorten the time needed to identify the best possible network structure. The modeling of self-induced vibrations allows analyzing how the vibrations come into being. This in turn makes it possible to develop effective ways of eliminating these vibrations and, ultimately, designing a practical control system that would dispose of the vibrations altogether.

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