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  2. Phase margin - Wikipedia

    en.wikipedia.org/wiki/Phase_margin

    A phase margin of 60 degrees is also a magic number because it allows for the fastest settling time when attempting to follow a voltage step input (a Butterworth design). An amplifier with lower phase margin will ring [nb 1] for longer and an amplifier with more phase margin will take a longer time to rise to the voltage step's final level.

  3. Step response - Wikipedia

    en.wikipedia.org/wiki/Step_response

    Figure 5: Bode gain plot to find phase margin; scales are logarithmic, so labeled separations are multiplicative factors. For example, f 0 dB = βA 0 × f 1. Next, the choice of pole ratio τ 1 /τ 2 is related to the phase margin of the feedback amplifier. [9] The procedure outlined in the Bode plot article is followed. Figure 5 is the Bode ...

  4. Root locus analysis - Wikipedia

    en.wikipedia.org/wiki/Root_locus_analysis

    Spirule. In control theory and stability theory, root locus analysis is a graphical method for examining how the roots of a system change with variation of a certain system parameter, commonly a gain within a feedback system.

  5. Bode plot - Wikipedia

    en.wikipedia.org/wiki/Bode_plot

    Figures 8 and 9 illustrate the gain margin and phase margin for a different amount of feedback β. The feedback factor is chosen smaller than in Figure 6 or 7, moving the condition | β A OL | = 1 to lower frequency. In this example, 1 / β = 77 dB, and at low frequencies A FB ≈ 77 dB as well. Figure 8 shows the gain plot.

  6. Nichols plot - Wikipedia

    en.wikipedia.org/wiki/Nichols_plot

    A Nichols plot. The Nichols plot is a plot used in signal processing and control design, named after American engineer Nathaniel B. Nichols. [1] [2] [3] It plots the phase response versus the response magnitude of a transfer function for any given frequency, and as such is useful in characterizing a system's frequency response.

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  9. Linear–quadratic regulator - Wikipedia

    en.wikipedia.org/wiki/Linear–quadratic_regulator

    LQR controllers possess inherent robustness with guaranteed gain and phase margin, [1] and they also are part of the solution to the LQG (linear–quadratic–Gaussian) problem. Like the LQR problem itself, the LQG problem is one of the most fundamental problems in control theory .