Modeling 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.
1. 2.1 Introduction - p. 25 2. 2.2 Basic concepts - p. 25 3. 2.3 Virtual work principle - p. 27 4. 2.4 Hamiltons principle - p. 29 5. 2.5 Euler–Lagrange theorem - p. 32 6. 2.6 Lagranges method - p. 32 7. 2.6.1 Lagrange's equations for constrained systems - p. 41 8. 2.6.2 Viscous loss functiona - p. 43 9. 2.6.3 Lagrange's equations for a rigid body - p. 44 10. 2.7 Hamiltons method - p. 53 11. 2.7.1 Legendre's dual transformation - p. 53 12. 2.7.2 Applying Hamilton's method - p. 54 13. 2.8 Kane's equations - p. 62 14. 2.9 Exercises - p. 80 15. Bibliography - p. 81 16. Chapter 3 Input-output modeling - p. 83 17. Abstract - p. 83 18. 3.1 Introduction - p. 83 19. 3.2 Electrical systems - p. 84 20. 3.3 Mechanical systems - p. 107 21. 3.3.2 Analogous systems - p. 117 22. 3.4 Hydraulic systems - p. 124 23. 3.4.1 Basic elements and fundamental relations - p. 124 24. 3.4.2 Hydraulic valve - p. 135 25. 3.4.3 Hydraulic servomotors - p. 146 26. 3.4.4 Advantages and disadvantages of hydraulic systems - p. 155 27. 3.5 Pneumatic systems - p. 157 28. 3.5.1 Mathematical modeling of pneumatic systems - p. 157 29. 3.5.2 Basic principles for obtaining derivative and integral controllers - p. 173 30. 3.5.3 Comparison between pneumatic and hydraulic systems - p. 173 31. 3.6 Thermal systems - p. 174 32. 3.7 Electromechanical systems - p. 175 33. 3.8 Exercises - p. 182 34. Chapter 4 Modeling using bond graph - p. 185 35. Abstract - p. 185 36. 4.1 Introduction - p. 185 37. 4.2 Engineer multiports - p. 185 38. 4.3 Bond graph - p. 189 39. 4.4 Causality in multiport basic elements - p. 203 40. 4.5 Block diagram and causality - p. 206 41. 4.6 Pseudo-bond graph and thermal systems - p. 208 42. 4.7 System modeling - p. 211 43. 4.8 Augmenting the bond graph - p. 241 44. 4.9 Obtaining equations of the bond graph - p. 245 45. 4.10 Obtaining equations of the bond graph and algebraic loops - p. 252 46. 4.11 Obtaining equations of the bond graph and derivative causality - p. 256 47. 4.12 Exercises - p. 261 48. Chapter 5 Numerical modeling using fuzzy inference systems - p. 263 49. Abstract - p. 263 50. 5.1 Introduction - p. 263 51. 5.2 Definitions and terminology of fuzzy sets - p. 264 52. 5.3 Operations on fuzzy sets - p. 269 53. 5.4 Multidimensional reference spaces - p. 272 54. 5.5 Formulations and parametric relations of membership functions - p. 273 55. 5.6 Linguistic variables - p. 286 56. 5.7 Fuzzy if-then rules - p. 288 57. 5.8 Fuzzy reasoning - p. 290 58. 5.9 Fuzzy reasoning or approximate reasoning - p. 292 59. 5.9.5 Tsukamoto's fuzzy model - p. 301 60. 5.10 Exercises - p. 307 61. Bibliography - p. 310 62. Chapter 6 Verification methods and working with software - p. 311 63. Index - p. 409
Modeling 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.
1. 2.1 Introduction - p. 25 2. 2.2 Basic concepts - p. 25 3. 2.3 Virtual work principle - p. 27 4. 2.4 Hamiltons principle - p. 29 5. 2.5 Euler–Lagrange theorem - p. 32 6. 2.6 Lagranges method - p. 32 7. 2.6.1 Lagrange's equations for constrained systems - p. 41 8. 2.6.2 Viscous loss functiona - p. 43 9. 2.6.3 Lagrange's equations for a rigid body - p. 44 10. 2.7 Hamiltons method - p. 53 11. 2.7.1 Legendre's dual transformation - p. 53 12. 2.7.2 Applying Hamilton's method - p. 54 13. 2.8 Kane's equations - p. 62 14. 2.9 Exercises - p. 80 15. Bibliography - p. 81 16. Chapter 3 Input-output modeling - p. 83 17. Abstract - p. 83 18. 3.1 Introduction - p. 83 19. 3.2 Electrical systems - p. 84 20. 3.3 Mechanical systems - p. 107 21. 3.3.2 Analogous systems - p. 117 22. 3.4 Hydraulic systems - p. 124 23. 3.4.1 Basic elements and fundamental relations - p. 124 24. 3.4.2 Hydraulic valve - p. 135 25. 3.4.3 Hydraulic servomotors - p. 146 26. 3.4.4 Advantages and disadvantages of hydraulic systems - p. 155 27. 3.5 Pneumatic systems - p. 157 28. 3.5.1 Mathematical modeling of pneumatic systems - p. 157 29. 3.5.2 Basic principles for obtaining derivative and integral controllers - p. 173 30. 3.5.3 Comparison between pneumatic and hydraulic systems - p. 173 31. 3.6 Thermal systems - p. 174 32. 3.7 Electromechanical systems - p. 175 33. 3.8 Exercises - p. 182 34. Chapter 4 Modeling using bond graph - p. 185 35. Abstract - p. 185 36. 4.1 Introduction - p. 185 37. 4.2 Engineer multiports - p. 185 38. 4.3 Bond graph - p. 189 39. 4.4 Causality in multiport basic elements - p. 203 40. 4.5 Block diagram and causality - p. 206 41. 4.6 Pseudo-bond graph and thermal systems - p. 208 42. 4.7 System modeling - p. 211 43. 4.8 Augmenting the bond graph - p. 241 44. 4.9 Obtaining equations of the bond graph - p. 245 45. 4.10 Obtaining equations of the bond graph and algebraic loops - p. 252 46. 4.11 Obtaining equations of the bond graph and derivative causality - p. 256 47. 4.12 Exercises - p. 261 48. Chapter 5 Numerical modeling using fuzzy inference systems - p. 263 49. Abstract - p. 263 50. 5.1 Introduction - p. 263 51. 5.2 Definitions and terminology of fuzzy sets - p. 264 52. 5.3 Operations on fuzzy sets - p. 269 53. 5.4 Multidimensional reference spaces - p. 272 54. 5.5 Formulations and parametric relations of membership functions - p. 273 55. 5.6 Linguistic variables - p. 286 56. 5.7 Fuzzy if-then rules - p. 288 57. 5.8 Fuzzy reasoning - p. 290 58. 5.9 Fuzzy reasoning or approximate reasoning - p. 292 59. 5.9.5 Tsukamoto's fuzzy model - p. 301 60. 5.10 Exercises - p. 307 61. Bibliography - p. 310 62. Chapter 6 Verification methods and working with software - p. 311 63. Index - p. 409
