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Total Size:
23.8 MB
Info Hash:
29CA1B12772486C0C60803A074AE4483BCCBDA64
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Added:
April 20, 2026, 7:45 a.m.
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(Last updated: April 20, 2026, 7:49 a.m.)
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| Rivas F. Process Control with MatLAB-Simulink. A Guide for Beginners 2024.pdf | 23.8 MB |
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NOTE
SOURCE: Rivas F. Process Control with MatLAB-Simulink. A Guide for Beginners 2025
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COVER
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MEDIAINFO
Textbook in PDF format This book aims to serve as an academic manual designed to aid in understanding and applying key concepts in process control using MatLAB and its associated tools. Each chapter features a brief theoretical introduction to help students contextualize the step-by-step solved problems, which are coded in MatLAB. In some instances, the book also covers the use of Simulink and other MatLAB applications, such as System Identification, Control System Designer, and Response Optimizer. The manual seeks to strengthen knowledge in control theory through problem-based learning, which is essential in this field. The text progresses from basic concepts in classical control, such as linearization, Laplace transform, transfer function, and frequency response, to more advanced control theories like state-space representation and discrete control. Throughout, basic examples are solved to significantly enhance the understanding of concepts and their application to real-world systems. MatLAB stands as a cornerstone in the realm of process control teaching, empowering students and educators alike with a comprehensive suite of tools for modeling, analysis, and implementation of control systems. The integration of MatLAB into the curriculum has revolutionized the way process control concepts are taught and understood, offering a dynamic platform for exploration and experimentation. One of the most notable contributions of MatLAB to process control teaching is its robust support for system modeling and simulation. MatLAB's extensive library of built-in functions and toolboxes offers students access to a wide range of analysis and design techniques for control systems. From classical PID control to advanced model predictive control (MPC) algorithms, MatLAB provides students with the flexibility to explore various control strategies and methodologies, gaining insights into their performance and robustness in different scenarios
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