Motion Control of Underactuated Mechanical Systems [electronic resource] / by Javier Moreno-Valenzuela, Carlos Aguilar-Avelar.

Por: Moreno-Valenzuela, Javier [author.]Colaborador(es): Aguilar-Avelar, Carlos [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Intelligent Systems, Control and Automation: Science and Engineering ; 88Editor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XI, 223 p. 81 illus., 66 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319583198Tema(s): Control engineering | Robotics | Mechatronics | Mechanics | Mechanical engineering | Control, Robotics, Mechatronics | Classical Mechanics | Mechanical EngineeringFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 629.8 Clasificación LoC:TJ210.2-211.495TJ163.12Recursos en línea: Libro electrónicoTexto
Contenidos:
Preface -- Notation and Acronyms -- 1. Introduction -- 2. Identification of underactuated mechanical systems -- 3. Feedback linearization controller for arm trajectory tracking of the Furuta pendulum -- 4. Adaptive neural network controller for arm trajectory tracking of the Furuta pendulum -- 5. Feedback linearization controller for wheel trajectory tracking of the inertia wheel pendulum -- 6. Adaptive controllers for pendulum trajectory tracking of the inertia wheel pendulum -- Appendices -- References. .
En: Springer Nature eBookResumen: This volume is the first to present a unified perspective on the control of underactuated mechanical systems. Based on real-time implementation of parameter identification, this book provides a variety of algorithms for the Furuta pendulum and the inertia wheel pendulum, which are two-degrees-of-freedom mechanical systems. Specifically, this work addresses and solves the problem of motion control via trajectory tracking in one joint coordinate while another joint is regulated. Besides, discussions on extensions to higher degrees-of-freedom systems are given. The book, aimed at control engineers as well as graduate students, ranges from the problem of parameter identification of the studied systems to the practical implementation of sophisticated motion control algorithms. Offering real-world solutions to manage the control of underactuated systems, this book provides a concise tutorial on recent breakthroughs in the field, original procedures to achieve bounding of the error trajectories, convergence and gain tuning guidelines. .
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Preface -- Notation and Acronyms -- 1. Introduction -- 2. Identification of underactuated mechanical systems -- 3. Feedback linearization controller for arm trajectory tracking of the Furuta pendulum -- 4. Adaptive neural network controller for arm trajectory tracking of the Furuta pendulum -- 5. Feedback linearization controller for wheel trajectory tracking of the inertia wheel pendulum -- 6. Adaptive controllers for pendulum trajectory tracking of the inertia wheel pendulum -- Appendices -- References. .

This volume is the first to present a unified perspective on the control of underactuated mechanical systems. Based on real-time implementation of parameter identification, this book provides a variety of algorithms for the Furuta pendulum and the inertia wheel pendulum, which are two-degrees-of-freedom mechanical systems. Specifically, this work addresses and solves the problem of motion control via trajectory tracking in one joint coordinate while another joint is regulated. Besides, discussions on extensions to higher degrees-of-freedom systems are given. The book, aimed at control engineers as well as graduate students, ranges from the problem of parameter identification of the studied systems to the practical implementation of sophisticated motion control algorithms. Offering real-world solutions to manage the control of underactuated systems, this book provides a concise tutorial on recent breakthroughs in the field, original procedures to achieve bounding of the error trajectories, convergence and gain tuning guidelines. .

UABC ; Temporal ; 01/01/2021-12/31/2023.

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