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  1. 12 Mar 2023: A new version of the Optimization-Based Control (OBC) supplement is now complete and posted
  2. 24 Jul 2020: Copyedited version of FBS2e now available for download
  3. 28 Aug 2021: Links to first edition supplemental information added to chapter pages
  4. 30 Oct 2020: Notes on Linear Systems Theory updated (release 0.2.2)
  5. Admin
  6. Architecture and System Design
  7. Bibliography
  8. Biomolecular Feedback Systems
  9. Cruise control
  10. Domitilla Del Vecchio
  11. Dynamic Behavior
  12. Errata: 'a' in equation (14.13) should be 's'
  13. Errata: Example 8.10 missing factor of v, a1 and a2 flipped
  14. Examples
  15. Exercise: Exploring the dynamics of a rolling mill
  16. Exercise: Popular articles about control
  17. FBS release 3.1.5
  18. Fbs.py
  19. Feedback Principles
  20. Feedback Systems: An Introduction for Scientists and Engineers
  21. Figure 1.11: A feedback system for controlling the velocity of a vehicle
  22. Figure 1.18: Air–fuel controller based on selectors
  23. Figure 2.11: Response to a step change in the reference signal for a system with a PI controller having two degrees of freedom
  24. Figure 2.12: Responses of a static nonlinear system
  25. Figure 2.14: Responses of the systems with integral feedback
  26. Figure 2.19: System with positive feedback and saturation
  27. Figure 2.8: Step responses for a first-order, closed loop system with proportional and PI control
  28. Figure 2.9: Responses to a unit step change in the reference signal for different values of the design parameters
  29. Figure 3.11: Simulation of the forced spring–mass system with different simulation time constants
  30. Figure 3.12: Frequency response computed by measuring the response of individual sinusoids
  31. Figure 3.22: Queuing dynamics
  32. Figure 3.24: Consensus protocols for sensor networks
  33. Figure 3.26: The repressilator genetic regulatory network
  34. Figure 3.28: Response of a neuron to a current input
  35. Figure 3.2: Illustration of a state model
  36. Figure 3.4: Input/output response of a linear system
  37. Figure 3.8: Discrete-time simulation of the predator–prey model
  38. Figure 4.12: Internet congestion control
  39. Figure 4.13: Internet congestion control for N identical sources across a single link
  40. Figure 4.20: Simulation of the predator-prey system
  41. Figure 4.2: Torque curves for typical car engine
  42. Figure 4.3: Car with cruise control encountering a sloping road
  43. Figure 5.10: Phase portraits for a congestion control protocol running with N = 60 identical source computers
  44. Figure 5.11: Comparison between phase portraits for a nonlinear system and its linearization
  45. Figure 5.1: Response of a damped oscillator
  46. Figure 5.3: Phase portraits
  47. Figure 5.4: Equilibrium points for an inverted pendulum
  48. Figure 5.5: Phase portrait and time domain simulation for a system with a limit cycle
  49. Figure 5.6: Illustration of Lyapunov’s concept of a stable solution
  50. Figure 5.7: Phase portrait and time domain simulation for a system with a single stable equilibrium point
  51. Figure 5.8: Phase portrait and time domain simulation for a system with a single asymptotically stable equilibrium point
  52. Figure 5.9: Phase portrait and time domain simulation for a system with a single unstable equilibrium point
  53. Figure 6.14: Linear versus nonlinear response for a vehicle with PI cruise control
  54. Figure 6.1: Superposition of homogeneous and particular solutions
  55. Figure 6.5: Modes for a second-order system with real eigenvalues
  56. Figure 8.13: Vehicle steering using gain scheduling
  57. Frequency Domain Analysis
  58. Frequency Domain Design
  59. Fundamental Limits
  60. Introduction
  61. Karl J. Åström
  62. LST release 0.2.2
  63. Lecture: Introduction to Feedback and Control (Caltech, Fall 2008)
  64. Lecture: Introduction to Feedback and Control (Caltech, Spring 2024)
  65. Linear Systems
  66. Main Page
  67. OBC: Archived news
  68. Output Feedback
  69. PID Control
  70. Preface
  71. Question: Can a control system include a human operator as a component?
  72. Question: How are stability, performance and robustness different?
  73. Question: How can I go from a continuous time linear ODE to a discrete time representation?
  74. Question: How can we tell from the phase plots if the system is oscillating?
  75. Question: How do you know when your model is sufficiently complex?
  76. Question: In the predator prey example, where is the fox birth rate term?
  77. Question: What is "closed form"?
  78. Question: What is a state? How does one determine what is a state and what is not?
  79. Question: What is a stochastic system?
  80. Question: What is the advantage of having a model?
  81. Question: What is the definition of a system?
  82. Question: Why does the effective service rate f(x) go to zero when x = 0 in the example on queuing systems?
  83. Question: Why isn't there a term for the rabbit death rate besides being killed by the foxes?
  84. Robust Performance
  85. Software
  86. State Feedback
  87. Supplement: Linear Systems Theory
  88. Supplement: Networked Control Systems
  89. Supplement: Optimization-Based Control
  90. System Modeling
  91. Transfer Functions

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