Modeling and Simulation of Dynamical Systems
- 1st Edition - November 27, 2024
- Imprint: Academic Press
- Author: Payam Zarafshan
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 4 1 3 4 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 4 1 3 3 - 8
Modeling and Simulation of Dynamical Systems explores the common methods used in the modeling and simulation of dynamic systems, providing foundational information that is essent… Read more
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Request a sales quoteModeling and Simulation of Dynamical Systems explores the common methods used in the modeling and simulation of dynamic systems, providing foundational information that is essential for further research. A key feature of this title is its systematic separation and classification of various modeling methods, enabling readers to select their preferred approach after studying the initial chapter and becoming familiar with fundamental definitions. Another unique feature is the use of numerous examples and solved problems throughout the book to support a basic understanding of a system’s behavior.
This title is highly recommended for researchers, professionals, and students in mechanical, biosystems, and mechatronic engineering.
- Explores, in detail, the different methods of modeling dynamic systems
- Provides numerous examples and solved problems, which distinguishes this book from other reference titles in the field
- Renders information on modeling and simulating software
Engineers - Mechanical Engineering, Electrical Engineering, Mechatronics Engineering, Biosystems Engineering. Advanced Students - Mechanical Engineering, Electrical Engineering, Mechatronics Engineering, Biosystems Engineering
- Modeling and Simulation of Dynamical Systems
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Preface
- Chapter 1 Preliminary concepts
- Abstract
- Keywords
- 1.1 Introduction
- 1.2 Familiarity with the concepts of systems
- 1.3 State-space form equations
- 1.3.1 State-space form equations for SISO systems
- 1.3.2 State-space form equations for MIMO systems
- 1.4 Transfer function
- 1.4.1 Obtaining transfer function from state-space form
- 1.4.2 Obtaining state-space form from transfer function
- 1.5 Exercises
- Bibliography
- Chapter 2 Analytical modeling methods
- Abstract
- Keywords
- 2.1 Introduction
- 2.2 Basic concepts
- 2.2.1 Optimizing or balancing a function
- 2.3 Virtual work principle
- 2.4 Hamiltons principle
- 2.5 Euler–Lagrange theorem
- 2.6 Lagranges method
- 2.6.1 Lagrange's equations for constrained systems
- 2.6.2 Viscous loss functiona
- 2.6.3 Lagrange's equations for a rigid body
- 2.7 Hamiltons method
- 2.7.1 Legendre's dual transformation
- 2.7.2 Applying Hamilton's method
- 2.8 Kane's equations
- 2.9 Exercises
- Bibliography
- Chapter 3 Input-output modeling
- Abstract
- Keywords
- 3.1 Introduction
- 3.2 Electrical systems
- 3.2.1 Basic elements and fundamental relations
- 3.2.2 Components combination of electrical energy systems
- 3.2.3 Kirchhoff’s, node, and loop Laws
- 3.2.4 Amplifiers
- 3.2.5 Complex impedance
- 3.3 Mechanical systems
- 3.3.1 Basic elements and fundamental relations
- 3.3.2 Analogous systems
- 3.4 Hydraulic systems
- 3.4.1 Basic elements and fundamental relations
- 3.4.2 Hydraulic valve
- 3.4.3 Hydraulic servomotors
- 3.4.4 Advantages and disadvantages of hydraulic systems
- 3.5 Pneumatic systems
- 3.5.1 Mathematical modeling of pneumatic systems
- 3.5.2 Basic principles for obtaining derivative and integral controllers
- 3.5.3 Comparison between pneumatic and hydraulic systems
- 3.6 Thermal systems
- 3.7 Electromechanical systems
- 3.8 Exercises
- Chapter 4 Modeling using bond graph
- Abstract
- Keywords
- 4.1 Introduction
- 4.2 Engineer multiports
- 4.3 Bond graph
- 4.3.1 Basic one-port elements
- 4.3.2 Basic two-port elements
- 4.3.3 Three-port junction elements
- 4.4 Causality in multiport basic elements
- 4.5 Block diagram and causality
- 4.6 Pseudo-bond graph and thermal systems
- 4.7 System modeling
- 4.7.1 Electrical systems
- 4.7.2 Mechanical systems
- 4.7.3 Hydraulic systems
- 4.7.4 Transducers and combined systems
- 4.8 Augmenting the bond graph
- 4.9 Obtaining equations of the bond graph
- 4.10 Obtaining equations of the bond graph and algebraic loops
- 4.11 Obtaining equations of the bond graph and derivative causality
- 4.12 Exercises
- Chapter 5 Numerical modeling using fuzzy inference systems
- Abstract
- Keywords
- 5.1 Introduction
- 5.2 Definitions and terminology of fuzzy sets
- 5.2.1 Characteristic function
- 5.2.2 Fuzzy sets and membership functions
- 5.3 Operations on fuzzy sets
- 5.4 Multidimensional reference spaces
- 5.5 Formulations and parametric relations of membership functions
- 5.5.1 One-dimensional membership functions
- 5.5.2 Cylindrical extension of one-dimensional fuzzy functions
- 5.5.3 Projection of fuzzy set
- 5.5.4 Types of union, intersection, and complement
- 5.5.5 Definition of T-norm (triangular norm) operator
- 5.5.6 Several types of T-norm operators
- 5.5.7 S-norm (T-conorm) operators
- 5.5.8 Fuzzy conjunction relation
- 5.5.9 Fuzzy extension principle
- 5.5.10 Fuzzy relation
- 5.5.11 Composition of fuzzy relations
- 5.6 Linguistic variables
- 5.6.1 Definition of linguistic variables
- 5.7 Fuzzy if-then rules
- 5.7.1 Mamdani's fuzzy rules
- 5.8 Fuzzy reasoning
- 5.8.1 Generalized modus ponens
- 5.9 Fuzzy reasoning or approximate reasoning
- 5.9.1 Compositional rule of inference
- 5.9.2 Fuzzy inference
- 5.9.3 Mamdani's inference when the results of the rule are the fuzzy singleton set
- 5.9.4 Sugeno's fuzzy model
- 5.9.5 Tsukamoto's fuzzy model
- 5.10 Exercises
- Bibliography
- Chapter 6 Verification methods and working with software
- Abstract
- Keywords
- 6.1 Introduction
- 6.2 Familiarity with SimMechanics software
- 6.2.1 Introduction
- 6.2.2 Simulink
- 6.2.3 SimMechanics toolbox
- 6.2.4 Convert SolidWorks files to SimMechanics
- 6.2.5 Simulink solvers
- 6.3 Familiarity with Adams software
- 6.3.1 Introduction
- 6.3.2 Main parts of the software
- 6.3.3 Introduction of different environments of software
- 6.3.4 Familiarity with the MSC Adams software environment
- 6.3.5 Function keys
- 6.3.6 Main toolbox window
- 6.3.7 How to import a file in Adams
- 6.4 Familiarity with autodesk simulation CFD software
- 6.4.1 Introduction
- 6.4.2 Autodesk simulation CFD software environment
- 6.4.3 Features of autodesk simulation CFD software
- Index
- Edition: 1
- Published: November 27, 2024
- Imprint: Academic Press
- No. of pages: 550
- Language: English
- Paperback ISBN: 9780443241345
- eBook ISBN: 9780443241338
PZ
Payam Zarafshan
Payam Zarafshan is an associate professor and head of the AGRINS Lab, in the Department of Mechatronics Engineering, School of Intelligent Systems Engineering, College of Interdisciplinary Science and Technology, University of Tehran, Iran. Additionally, he is a lecturer in the School of Engineering, Design and Built Environment at Western Sydney University, Sydney, Australia. He received his PhD in Mechanical Engineering from K. N. Toosi University of Technology, Iran. His research has mainly focused on aerial and space systems and agriculture technologies by applying automation, robotics, and mechatronics. He is currently the founder and supervisor of the AGRicultural INtelligent System Laboratory (AGRINS Lab) based at the University of Tehran. He has supervised more than 28 MSc students and 3 PhD students in different mechatronic fields, including space robotic systems, irrigation systems, pruning cutters, water channel dredgers, aerial pollinators, cable robots, and greenhouse technologies.
Affiliations and expertise
Associate Professor, Head of AGRINS Lab., Department of Mechatronics Engineering, School of Intelligent Systems Engineering, College of Interdisciplinary Science and Technology, University of Tehran, Iran. Lecturer, School of Engineering, Design and Built Environment at Western Sydney University, Sydney, AustraliaRead Modeling and Simulation of Dynamical Systems on ScienceDirect