9 research outputs found
Advanced Control of Piezoelectric Actuators.
168 p.A lo largo de las últimas décadas, la ingeniería de precisión ha tenido un papel importante como tecnología puntera donde la tendencia a la reducción de tamaño de las herramientas industriales ha sido clave. Los procesos industriales comenzaron a demandar precisión en el rango de nanómetros a micrómetros. Pese a que los actuadores convencionales no pueden reducirse lo suficiente ni lograr tal exactitud, los actuadores piezoeléctricos son una tecnología innovadora en este campo y su rendimiento aún está en estudio en la comunidad científica. Los actuadores piezoeléctricos se usan comúnmente en micro y nanomecatrónica para aplicaciones de posicionamiento debido a su alta resolución y fuerza de actuación (pueden llegar a soportar fuerzas de hasta 100 Newtons) en comparación con su tamaño. Todas estas características también se pueden combinar con una actuación rápida y rigidez, según los requisitos de la aplicación. Por lo tanto, con estas características, los actuadores piezoeléctricos pueden ser utilizados en una amplia variedad de aplicaciones industriales. Los efectos negativos, como la fluencia, vibraciones y la histéresis, se estudian comúnmente para mejorar el rendimiento cuando se requiere una alta precisión. Uno de los efectos que más reduce el rendimiento de los PEA es la histéresis. Esto se produce especialmente cuando el actuador está en una aplicación de guiado, por lo que la histéresis puede inducir errores que pueden alcanzar un valor de hasta 22%. Este fenómeno no lineal se puede definir como un efecto generado por la combinación de acciones mecánicas y eléctricas que depende de estados previos. La histéresis se puede reducir principalmente mediante dos estrategias: rediseño de materiales o algoritmos de control tipo feedback. El rediseño de material comprende varias desventajas por lo que el motivo principal de esta tesis está enfocado al diseño de algoritmos de control para reducir la histéresis. El objetivo principal de esta tesis es el desarrollo de estrategias de control avanzadas que puedan mejorar la precisión de seguimiento de los actuadores piezoeléctricos comerciale
Data-Driven Model-Free Sliding Mode and Fuzzy Control with Experimental Validation
The paper presents the combination of the model-free control technique with two popular nonlinear control techniques, sliding mode control and fuzzy control. Two data-driven model-free sliding mode control structures and one data-driven model-free fuzzy control structure are given. The data-driven model-free sliding mode control structures are built upon a model-free intelligent Proportional-Integral (iPI) control system structure, where an augmented control signal is inserted in the iPI control law to deal with the error dynamics in terms of sliding mode control. The data-driven model-free fuzzy control structure is developed by fuzzifying the PI component of the continuous-time iPI control law. The design approaches of the data-driven model-free control algorithms are offered. The data-driven model-free control algorithms are validated as controllers by real-time experiments conducted on 3D crane system laboratory equipment
Computational Intelligence in Electromyography Analysis
Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research
Pattern recognition-based real-time myoelectric control for anthropomorphic robotic systems : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Mechatronics at Massey University, Manawatū, New Zealand
All copyrighted Figures have been removed but may be accessed via their source cited in their respective captions.Advanced human-computer interaction (HCI) or human-machine interaction (HMI) aims to help
humans interact with computers smartly. Biosignal-based technology is one of the most promising
approaches in developing intelligent HCI systems. As a means of convenient and non-invasive
biosignal-based intelligent control, myoelectric control identifies human movement intentions from
electromyogram (EMG) signals recorded on muscles to realise intelligent control of robotic systems.
Although the history of myoelectric control research has been more than half a century, commercial
myoelectric-controlled devices are still mostly based on those early threshold-based methods. The
emerging pattern recognition-based myoelectric control has remained an active research topic in
laboratories because of insufficient reliability and robustness. This research focuses on pattern
recognition-based myoelectric control. Up to now, most of effort in pattern recognition-based
myoelectric control research has been invested in improving EMG pattern classification accuracy.
However, high classification accuracy cannot directly lead to high controllability and usability for
EMG-driven systems. This suggests that a complete system that is composed of relevant modules,
including EMG acquisition, pattern recognition-based gesture discrimination, output equipment and its
controller, is desirable and helpful as a developing and validating platform that is able to closely emulate
real-world situations to promote research in myoelectric control.
This research aims at investigating feasible and effective EMG signal processing and pattern
recognition methods to extract useful information contained in EMG signals to establish an intelligent,
compact and economical biosignal-based robotic control system. The research work includes in-depth
study on existing pattern recognition-based methodologies, investigation on effective EMG signal
capturing and data processing, EMG-based control system development, and anthropomorphic robotic
hand design. The contributions of this research are mainly in following three aspects:
Developed precision electronic surface EMG (sEMG) acquisition methods that are able to
collect high quality sEMG signals. The first method was designed in a single-ended signalling
manner by using monolithic instrumentation amplifiers to determine and evaluate the analog
sEMG signal processing chain architecture and circuit parameters. This method was then
evolved into a fully differential analog sEMG detection and collection method that uses
common commercial electronic components to implement all analog sEMG amplification and
filtering stages in a fully differential way. The proposed fully differential sEMG detection and collection method is capable of offering a higher signal-to-noise ratio in noisy environments
than the single-ended method by making full use of inherent common-mode noise rejection
capability of balanced signalling. To the best of my knowledge, the literature study has not
found similar methods that implement the entire analog sEMG amplification and filtering chain
in a fully differential way by using common commercial electronic components.
Investigated and developed a reliable EMG pattern recognition-based real-time gesture
discrimination approach. Necessary functional modules for real-time gesture discrimination
were identified and implemented using appropriate algorithms. Special attention was paid to
the investigation and comparison of representative features and classifiers for improving
accuracy and robustness. A novel EMG feature set was proposed to improve the performance
of EMG pattern recognition.
Designed an anthropomorphic robotic hand construction methodology for myoelectric control
validation on a physical platform similar to in real-world situations. The natural anatomical
structure of the human hand was imitated to kinematically model the robotic hand. The
proposed robotic hand is a highly underactuated mechanism, featuring 14 degrees of freedom
and three degrees of actuation.
This research carried out an in-depth investigation into EMG data acquisition and EMG signal pattern
recognition. A series of experiments were conducted in EMG signal processing and system
development. The final myoelectric-controlled robotic hand system and the system testing confirmed
the effectiveness of the proposed methods for surface EMG acquisition and human hand gesture
discrimination. To verify and demonstrate the proposed myoelectric control system, real-time tests were
conducted onto the anthropomorphic prototype robotic hand. Currently, the system is able to identify
five patterns in real time, including hand open, hand close, wrist flexion, wrist extension and the rest
state. With more motion patterns added in, this system has the potential to identify more hand
movements. The research has generated a few journal and international conference publications
Faculty Publications and Creative Works 1999
One of the ways in which we recognize our faculty at the University of New Mexico is through Faculty Publications & Creative Works. An annual publication, it highlights our faculty\u27s scholarly and creative activities and achievements and serves as a compendium of UNM faculty efforts during the 1999 calendar year. Faculty Publications & Creative Works strives to illustrate the depth and breadth of research activities performed throughout our University\u27s laboratories, studios and classrooms. We believe that the communication of individual research is a significant method of sharing concepts and thoughts and ultimately inspiring the birth of new ideas. In support of this, UNM faculty during 1999 produced over 2,292 works, including 1,837 scholarly papers and articles, 78 books, 82 book chapters, 175 reviews, 113 creative works and 7 patented works. We are proud of the accomplishments of our faculty which are in part reflected in this book, which illustrates the diversity of intellectual pursuits in support of research and education at the University of New Mexico
Energy, Science and Technology 2015. The energy conference for scientists and researchers. Book of Abstracts, EST, Energy Science Technology, International Conference & Exhibition, 20-22 May 2015, Karlsruhe, Germany
We are pleased to present you this Book of Abstracts, which contains the submitted contributions to the "Energy, Science and Technology Conference & Exhibition EST 2015". The EST 2015 took place from May, 20th until May, 22nd 2015 in Karlsruhe, Germany, and brought together many different stakeholders, who do research or work in the broad field of "Energy".
Renewable energies have to present a relevant share in a sustainable energy system and energy efficiency has to guarantee that conventional as well as renewable energy sources are transformed and used in a reasonable way. The adaption of existing infrastructure and the establishment of new systems, storages and grids are necessary to face the challenges of a changing energy sector. Those three main topics have been the fundament of the EST 2015, which served as a platform for national and international attendees to discuss and interconnect the various disciplines within energy research and energy business.
We thank the authors, who summarised their high-quality and important results and experiences within one-paged abstracts and made the conference and this book possible. The abstracts of this book have been peer-reviewed by an international Scientific Programme Committee and are ordered by type of presentation (oral or poster) and topics. You can navigate by using either the table of contents (page 3) or the conference programme (starting page 4 for oral presentations and page 21 for posters respectively)