Multicriteria fuzzy-polynomial observer design for a 3DoF nonlinear electromechanical platform

Pitarch, José Luis; Sala, Antonio

doi:10.1016/j.engappai.2013.11.006

Cited by 10 publications

(3 citation statements)

References 21 publications

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“…Examples can be seen in Pitarch and Sala (2014); Sala et al (2011). The proof can be obtained easily by setting up the increment V = V k+1 − V k and applying Schur complement.…”

Section: Observer Designmentioning

confidence: 99%

Fuzzy Modeling and Control: Theory and Applications

Mata¹,

Marichal²,

Jimnez³

2014

Atlantis Computational Intelligence Systems

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Aims and scope of the seriesThe series 'Atlantis Computational Intelligence Systems' aims at covering state-of-the-art research and development in all fields where computational intelligence is investigated and applied. The series seeks to publish monographs and edited volumes on foundations and new developments in the field of computational intelligence, including fundamental and applied research as well as work describing new, emerging technologies originating from computational intelligence research. Applied CI research may range from CI applications in the industry to research projects in the life sciences, including research in biology, physics, chemistry and the neurosciences.All books in this series are co-published with Springer.For more information on this series and our other book series, please visit our website at: www.atlantis-press.com/publications/books. This book is published under the Creative Commons Attribution-Non-commercial license, meaning that copying, distribution, transmitting and adapting the book is permitted, provided that this is done for non-commercial purposes and that the book is attributed. This book, or any parts thereof, may not be reproduced for commercial purposes in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system known or to be invented, without prior permission from the Publisher.Printed on acid-free paper ForewordAlmost half a century has passed since the publication of the seminal paper by Prof. Lotfi A. Zadeh. Fifty years that have witnessed an impressive growth of fuzzy systems from both the theoretical and applied points of view. Impressive growth and at the same time following an unforeseen way, since as Prof. Zadeh has said many times, his expectations when writing his first paper on fuzzy sets in 1965 were that fuzzy sets would find its main applications in the realm of humanistic systems (economics, linguistics, psychology, etc.). Now the reality is that most of the success of fuzzy systems research (at least in its initial decades) was related to its application to mechanistic instead of humanistic systems. This book concentrates on modeling and control of mechanistic systems, as can be seen when reading the Table of Contents, first considering important theoretical aspects and then showing its application to quite interesting real-world problems.Any book on fuzzy modeling and control is somehow a tribute to those who paved the way for the topic. In this case, we need to consider three key persons and three related milestones in the history of fuzzy sets. First, the already mentioned Prof. Zadeh and his 1973 paper ''Outline of a New Approach to the Analysis of Complex Systems and Decision Processes,'' IEEE Transactions on Systems, Man, and Cybernetics 3: 28-44 (1973), the paper where concepts as linguistic variable and fuzzy if-then rules took form, and at the same time, the paper that triggered the second hint in the road to build up the theory of fuzzy modeling and control. Ab...

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“…Examples can be seen in Pitarch and Sala (2014); Sala et al (2011). The proof can be obtained easily by setting up the increment V = V k+1 − V k and applying Schur complement.…”

Section: Observer Designmentioning

confidence: 99%

Fuzzy Modeling and Control: Theory and Applications

Mata¹,

Marichal²,

Jimnez³

2014

Atlantis Computational Intelligence Systems

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“…The experimental results presented in this chapter have been published in the journal paper Pitarch and Sala (2014).…”

Section: Albert Einsteinmentioning

confidence: 96%

“…In this case, a trade-off between H ∞ norm bounds and speed of convergence performance is taken into account in the design process: H ∞ is a worst-case measure (of disturbance/model error rejection) so its solutions are conservative in practice whereas decay-rate optimization produces unacceptable noisy estimates. The theoretical results presented in this section have been used for the experimental applications (Part III of the thesis) and appear published in the journal paper Pitarch and Sala (2014). Both continuous-time and discrete-time design methodologies can be pursued in order to obtain an observer with the objective of achieving acceptable behaviour in practice.…”

Section: H ∞ Polynomial Observer Designmentioning

confidence: 99%

Contributions to fuzzy polynomial techniques for stability analysis and control

Pérez¹,

Luis²

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Support from the French Laboratory LAMIH UMR CNRS8530 from the Université de Valenciennes et du Hainaut-Cambrésis is also acknowledged, both for accepting the author in its facilities as pre-doctoral stay and for its valuable collaboration sharing knowledge and data for the experimental applications presented on this thesis.The author thanks also the Control of Complex Systems Group from the Universitat Politècnica de València for the use of the group's infrastructure, in particular computational resources (Carraixet server).To all the people who decided getting out of my life by their own decision, because their absence provided me with more time for working and, of course, to you, expensive reader. AgradecimientosHan sido cuatro duros, pero a la vez amenos, años de trabajo para dar su fruto en esta tesis doctoral. Por lo tanto, hay muchas personas que, en mayor o menor medida, han contribuido de alguna forma a que este trabajo se haya llevado a buen puerto y voy a tener que rogar me disculpen por no haber sido capaz de acordarme de todos/as en estas lineas. En primer lugar, como no podría ser de otra forma, quiero agradecer a mi director de tesis, Antonio Sala, por todo lo que se le presupone a un director (transferencia de conocimiento en la materia, disponibilidad, supervisión del trabajo, trazado de guias principales, etc) y sobre todo por lo que no se le presupone: humildad, cercanía, paciencia infinita, sinceridad y consejos, incluso sobre aspectos de la vida que están fuera del ambito exclusivo del doctorado. Por ser verdaderamente un profesor para mi, gracias Antonio.Asimismo, quiero agradecer profundamente a Carlos Ariño por estar siempre disponible para explicarme cosas, aportar ideas y revisar mi trabajo, cuando oficialmente no tenía ninguna obligación para ello.Tampoco sería justo que en estas lineas me olvidara de Nacho Peñarrocha, mi director de proyecto final de carrera, a quien no pude agradecer en su momento por reglas de formato en el manuscrito. Probablemente, si Nacho no hubiera impartido las prácticas de Sistemas Automáticos en 2006, no me hubiera dirigido el PFC, o no me hubiera animado a solicitar la beca FPI, no estaría escribiendo estas lineas en mi tesis ahora.Espero, en algún momento y de alguna manera, ser capaz de devolveros a los tres todo el esfuerzo y dedicación que empleasteis en mi formación como investigador, como ingeniero y como persona.En segundo lugar, estoy especialmente agradecido a Thierry-Marie Guerra por haberme permitido trabajar tres meses en las instalaciones del LAMIH y tratarme como un investigador invitado en lugar de como un estudiante predoctoral. De la misma forma, quiero agradecer a Jimmy Lauber por aceptar ix x AGRADECIMIENTOS supervisar mi trabajo, colaborar conmigo y, para ello, sacar tiempo de donde no tenía.En tercer lugar, quiero agradecer de forma especial a Alejandro Vignoni, quien ha sido compañero de fatigas durante estos ultimos tres años y a quien le debo el aprender a moverme por el mundo, perdiendo el miedo a vivir fuera de mi termo particular....

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Stabilization of a quadrotor system using an optimal neural network controller

Farzaneh

Tavakolpour-Saleh

2021

J Braz. Soc. Mech. Sci. Eng.

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Multicriteria fuzzy-polynomial observer design for a 3DoF nonlinear electromechanical platform

Cited by 10 publications

References 21 publications

Fuzzy Modeling and Control: Theory and Applications

Fuzzy Modeling and Control: Theory and Applications

Contributions to fuzzy polynomial techniques for stability analysis and control

Stabilization of a quadrotor system using an optimal neural network controller

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