Patrick O J Kaltjob - Control of Mechatronic Systems: Model-Driven Design and Implementation Guidelines

1. Chapter 1
2. Chapter 2
3. Chapter 3
4. Chapter 4
5. Chapter 5
6. Chapter 6
7. Chapter 7
8. Chapter 8
9. Appendix A
10. Appendix B
11. Appendix C

1. Chapter 1
2. Chapter 2
3. Chapter 3
4. Chapter 4
5. Chapter 5
6. Chapter 6
7. Chapter 7
8. Chapter 8
9. Appendix E

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Patrick O.J. Kaltjob

Ecole Nationale Superieure Polytechnique

Yaounde, Cameroun

This edition first published 2019

2019 John Wiley & Sons Ltd

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Library of Congress Cataloging-in-Publication Data

Names: Kaltjob, Patrick O. J., author.

Title: Control of mechatronic systems : model-driven design and implementation guidelines / Patrick O. J. Kaltjob.

Description: Hoboken, NJ : John Wiley & Sons, 2020. | Includes bibliographical references and index.

Identifiers: LCCN 2018051541 (print) | LCCN 2019022413 (ebook) | ISBN 9781119505808 (hardcover)

Subjects: LCSH: Mechatronics. | Manufacturing processes.

Classification: LCC TJ163.12 .K34 2019 (print) | LCC TJ163.12 (ebook) | DDC 621dc23

LC record available at https://lccn.loc.gov/2018051541

LC ebook record available at https://lccn.loc.gov/2019022413

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To Aaron, Thomas, Olive and Anne

The control of mechatronic systems and electrical-driven processes aims to provide tools to ensure their operating performance in terms of productivity, optimization, reliability, safety, continuous operations and even stability. This is usually achieved through hybrid control paradigms using digital or analog tools. Nowadays, digital tools are widely considered to implement control systems as they offer numerous advantages including their ability: (i) to ease the control system implementation; (ii) to design complex and built-in intelligent information processing combining multiple functions for control, fault detection and diagnostic, monitoring and planning decisions; (iii) to integrate logic and continuous control algorithms as well as supervision programs into hybrid control strategies; (iv) to enhance the synchronization of input and output process operations; (v) to coordinate control actions among geographically distributed systems and processes and (iv) to achieve reliable and optimal operating conditions.

The digital control system architecture usually consists of the integration of the following functional units: a data processing and computing unit, an electrical-driven actuating unit, a measuring and detecting unit, a data acquisition ( DAQ ) and transmitting unit and a signal conditioning unit. The data processing and computing unit can be implemented through devices such as microcontroller ( C ), programmable logic controller ( PLC ) with a control function, digital signal processing ( DSP )a and a field-programmable gate array ( FPGA ).

The design of efficient control systems requires the mathematical modeling of mechatronic systems and process dynamics. This can be achieved in accordance with the operating characteristics (discrete and continuous) and objectives as well as technological constraints of the related instrumentation (signal conversion, transmission, conditioning, measurement, actuation etc.). However, in most of the current engineering literature on the design of digital control systems, the mathematical foundation of discrete time and discrete event systems is usually presented separately from the technological constraints of control instrumentation. For example, the operating time delay models or signal to noise ratio from digital device interfaces are not usually considered. Hence, the theoretical control algorithms proposed have limited practical applicability.

Challenges in the development of a practical design approach for the control of mechatronic systems and electrical-driven processes are: (i) to size and select control instrumentation in accordance with controlled system design objectives; (ii) to develop accordingly the mathematical discrete hybrid model capturing their continuous and discrete event behavioristic characteristics and (iii) to integrate the control systems with respect to technological constraints and operational characterization (discrete and continuous) (e.g. time delays, signal to noise ratios etc.).