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

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