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Bode plot

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Graph of the frequency response of a control system
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Figure 1A:High-pass filter (1st-order, one-pole) Bode magnitude plot (top) and Bode phase plot (bottom). The red data curve is approximated by the straight black line.
Figure 1B:Low-pass filter (1st-order, one-pole) Bode magnitude plot (top) and Bode phase plot (bottom). The red data curve is approximated by the straight black line.

Inelectrical engineering andcontrol theory, aBode plot is agraph of thefrequency response of a system. It is usually a combination of aBode magnitude plot, expressing the magnitude (usually indecibels) of the frequency response, and aBode phase plot, expressing thephase shift.

As originally conceived byHendrik Wade Bode in the 1930s, the plot is anasymptoticapproximation of the frequency response,using straight line segments.[1]

Overview

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Among his several important contributions tocircuit theory andcontrol theory, engineerHendrik Wade Bode, while working atBell Labs in the 1930s, devised a simple but accurate method for graphinggain and phase-shift plots. These bear his name,Bode gain plot andBode phase plot. "Bode" is often pronounced as[ˈboːdə] which is a Dutch pronunciation, closer to English/ˈbdə/BOH-d.[2][3]

Bode was faced with the problem of designing stableamplifiers withfeedback for use in telephone networks. He developed the graphical design technique of the Bode plots to show thegain margin andphase margin required to maintain stability under variations in circuit characteristics caused during manufacture or during operation.[4] The principles developed were applied to design problems ofservomechanisms and other feedback control systems. The Bode plot is an example of analysis in thefrequency domain.

Definition

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The Bode plot for alinear, time-invariant system withtransfer functionH(s){\displaystyle H(s)} (s{\displaystyle s} being the complex frequency in theLaplace domain) consists of a magnitude plot and a phase plot.

TheBode magnitude plot is the graph of the function|H(s=jω)|{\displaystyle |H(s=j\omega )|} of frequencyω{\displaystyle \omega } (withj{\displaystyle j} being theimaginary unit). Theω{\displaystyle \omega }-axis of the magnitude plot is logarithmic and the magnitude is given indecibels, i.e., a value for the magnitude|H|{\displaystyle |H|} is plotted on the axis at20log10|H|{\displaystyle 20\log _{10}|H|}.

TheBode phase plot is the graph of thephase, commonly expressed in degrees, of theargument functionarg(H(s=jω)){\displaystyle \arg \left(H(s=j\omega )\right)} as a function ofω{\displaystyle \omega }. The phase is plotted on the same logarithmicω{\displaystyle \omega }-axis as the magnitude plot, but the value for the phase is plotted on a linear vertical axis.

Frequency response

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This section illustrates that a Bode plot is a visualization of the frequency response of a system.

Consider alinear, time-invariant system with transfer functionH(s){\displaystyle H(s)}. Assume that the system is subject to a sinusoidal input with frequencyω{\displaystyle \omega },

u(t)=sin(ωt),{\displaystyle u(t)=\sin(\omega t),}

that is applied persistently, i.e. from a time{\displaystyle -\infty } to a timet{\displaystyle t}. The response will be of the form

y(t)=y0sin(ωt+φ),{\displaystyle y(t)=y_{0}\sin(\omega t+\varphi ),}

i.e., also a sinusoidal signal with amplitudey0{\displaystyle y_{0}} shifted by a phaseφ{\displaystyle \varphi } with respect to the input.

It can be shown[5] that the magnitude of the response is

y0=|H(jω)|{\displaystyle y_{0}=|H(\mathrm {j} \omega )|}1

and that the phase shift is

φ=argH(jω).{\displaystyle \varphi =\arg H(\mathrm {j} \omega ).}2

In summary, subjected to an input with frequencyω{\displaystyle \omega }, the system responds at the same frequency with an output that is amplified by a factor|H(jω)|{\displaystyle |H(\mathrm {j} \omega )|} and phase-shifted byargH(jω){\displaystyle \arg H(\mathrm {j} \omega )}. These quantities, thus, characterize the frequency response and are shown in the Bode plot.

Rules for handmade Bode plot

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For many practical problems, the detailed Bode plots can be approximated with straight-line segments that areasymptotes of the precise response. The effect of each of the terms of a multiple elementtransfer function can be approximated by a set of straight lines on a Bode plot. This allows a graphical solution of the overall frequency response function. Before widespread availability of digital computers, graphical methods were extensively used to reduce the need for tedious calculation; a graphical solution could be used to identify feasible ranges of parameters for a new design.

The premise of a Bode plot is that one can consider the log of a function in the form

f(x)=A(xcn)an{\displaystyle f(x)=A\prod (x-c_{n})^{a_{n}}}

as a sum of the logs of itszeros and poles:

log(f(x))=log(A)+anlog(xcn).{\displaystyle \log(f(x))=\log(A)+\sum a_{n}\log(x-c_{n}).}

This idea is used explicitly in the method for drawing phase diagrams. The method for drawing amplitude plots implicitly uses this idea, but since the log of the amplitude of each pole or zero always starts at zero and only has one asymptote change (the straight lines), the method can be simplified.

Straight-line amplitude plot

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Amplitude decibels is usually done usingdB=20log10(X){\displaystyle {\text{dB}}=20\log _{10}(X)} to define decibels. Given a transfer function in the form

H(s)=A(sxn)an(syn)bn,{\displaystyle H(s)=A\prod {\frac {(s-x_{n})^{a_{n}}}{(s-y_{n})^{b_{n}}}},}

wherexn{\displaystyle x_{n}} andyn{\displaystyle y_{n}} are constants,s=jω{\displaystyle s=\mathrm {j} \omega },an,bn>0{\displaystyle a_{n},b_{n}>0}, andH{\displaystyle H} is the transfer function:

To handle irreducible 2nd-order polynomials,ax2+bx+c{\displaystyle ax^{2}+bx+c} can, in many cases, be approximated as(ax+c)2{\displaystyle ({\sqrt {a}}x+{\sqrt {c}})^{2}}.

Note that zeros and poles happen whenω{\displaystyle \omega } isequal to a certainxn{\displaystyle x_{n}} oryn{\displaystyle y_{n}}. This is because the function in question is the magnitude ofH(jω){\displaystyle H(\mathrm {j} \omega )}, and since it is a complex function,|H(jω)|=HH{\displaystyle |H(\mathrm {j} \omega )|={\sqrt {H\cdot H^{*}}}}. Thus at any place where there is a zero or pole involving the term(s+xn){\displaystyle (s+x_{n})}, the magnitude of that term is(xn+jω)(xnjω)=xn2+ω2{\displaystyle {\sqrt {(x_{n}+\mathrm {j} \omega )(x_{n}-\mathrm {j} \omega )}}={\sqrt {x_{n}^{2}+\omega ^{2}}}}.

Corrected amplitude plot

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To correct a straight-line amplitude plot:

Note that this correction method does not incorporate how to handle complex values ofxn{\displaystyle x_{n}} oryn{\displaystyle y_{n}}. In the case of an irreducible polynomial, the best way to correct the plot is to actually calculate the magnitude of the transfer function at the pole or zero corresponding to the irreducible polynomial, and put that dot over or under the line at that pole or zero.

Straight-line phase plot

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Given a transfer function in the same form as above,

H(s)=A(sxn)an(syn)bn,{\displaystyle H(s)=A\prod {\frac {(s-x_{n})^{a_{n}}}{(s-y_{n})^{b_{n}}}},}

the idea is to draw separate plots for each pole and zero, then add them up. The actual phase curve is given by

φ(s)=arctanIm[H(s)]Re[H(s)].{\displaystyle \varphi (s)=-\arctan {\frac {\operatorname {Im} [H(s)]}{\operatorname {Re} [H(s)]}}.}

To draw the phase plot, foreach pole and zero:

Example

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To create a straight-line plot for a first-order (one-pole) low-pass filter, one considers the normalized form of the transfer function in terms of the angular frequency:

Hlp(jω)=11+jωωc.{\displaystyle H_{\text{lp}}(\mathrm {j} \omega )={\frac {1}{1+\mathrm {j} {\frac {\omega }{\omega _{\text{c}}}}}}.}

The Bode plot is shown in Figure 1(b) above, and construction of the straight-line approximation is discussed next.

Magnitude plot

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The magnitude (indecibels) of the transfer function above (normalized and converted to angular-frequency form), given by the decibel gain expressionAvdB{\displaystyle A_{\text{vdB}}}:

AvdB=20log|Hlp(jω)|=20log1|1+jωωc|=20log|1+jωωc|=10log(1+ω2ωc2).{\displaystyle {\begin{aligned}A_{\text{vdB}}&=20\log |H_{\text{lp}}(\mathrm {j} \omega )|\\&=20\log {\frac {1}{\left|1+\mathrm {j} {\frac {\omega }{\omega _{\text{c}}}}\right|}}\\&=-20\log \left|1+\mathrm {j} {\frac {\omega }{\omega _{\text{c}}}}\right|\\&=-10\log \left(1+{\frac {\omega ^{2}}{\omega _{\text{c}}^{2}}}\right).\end{aligned}}}

Then plotted versus input frequencyω{\displaystyle \omega } on a logarithmic scale, can be approximated bytwo lines, forming the asymptotic (approximate) magnitude Bode plot of the transfer function:

These two lines meet at thecorner frequencyωc{\displaystyle \omega _{\text{c}}}. From the plot, it can be seen that for frequencies well below the corner frequency, the circuit has an attenuation of 0 dB, corresponding to a unity pass-band gain, i.e. the amplitude of the filter output equals the amplitude of the input. Frequencies above the corner frequency are attenuated – the higher the frequency, the higher theattenuation.

Phase plot

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The phase Bode plot is obtained by plotting the phase angle of the transfer function given by

argHlp(jω)=tan1ωωc{\displaystyle \arg H_{\text{lp}}(\mathrm {j} \omega )=-\tan ^{-1}{\frac {\omega }{\omega _{\text{c}}}}}

versusω{\displaystyle \omega }, whereω{\displaystyle \omega } andωc{\displaystyle \omega _{\text{c}}} are the input and cutoff angular frequencies respectively. For input frequencies much lower than corner, the ratioω/ωc{\displaystyle \omega /\omega _{\text{c}}} is small, and therefore the phase angle is close to zero. As the ratio increases, the absolute value of the phase increases and becomes −45° whenω=ωc{\displaystyle \omega =\omega _{\text{c}}}. As the ratio increases for input frequencies much greater than the corner frequency, the phase angle asymptotically approaches −90°. The frequency scale for the phase plot is logarithmic.

Normalized plot

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The horizontal frequency axis, in both the magnitude and phase plots, can be replaced by the normalized (nondimensional) frequency ratioω/ωc{\displaystyle \omega /\omega _{\text{c}}}. In such a case the plot is said to be normalized, and units of the frequencies are no longer used, since all input frequencies are now expressed as multiples of the cutoff frequencyωc{\displaystyle \omega _{\text{c}}}.

An example with zero and pole

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Figures 2-5 further illustrate construction of Bode plots. This example with both a pole and a zero shows how to use superposition. To begin, the components are presented separately.

Figure 2 shows the Bode magnitude plot for a zero and a low-pass pole, and compares the two with the Bode straight line plots. The straight-line plots are horizontal up to the pole (zero) location and then drop (rise) at 20 dB/decade. The second Figure 3 does the same for the phase. The phase plots are horizontal up to a frequency factor of ten below the pole (zero) location and then drop (rise) at 45°/decade until the frequency is ten times higher than the pole (zero) location. The plots then are again horizontal at higher frequencies at a final, total phase change of 90°.

Figure 4 and Figure 5 show how superposition (simple addition) of a pole and zero plot is done. The Bode straight line plots again are compared with the exact plots. The zero has been moved to higher frequency than the pole to make a more interesting example. Notice in Figure 4 that the 20 dB/decade drop of the pole is arrested by the 20 dB/decade rise of the zero resulting in a horizontal magnitude plot for frequencies above the zero location. Notice in Figure 5 in the phase plot that the straight-line approximation is pretty approximate in the region where both pole and zero affect the phase. Notice also in Figure 5 that the range of frequencies where the phase changes in the straight line plot is limited to frequencies a factor of ten above and below the pole (zero) location. Where the phase of the pole and the zero both are present, the straight-line phase plot is horizontal because the 45°/decade drop of the pole is arrested by the overlapping 45°/decade rise of the zero in the limited range of frequencies where both are active contributors to the phase.

  • Example with pole and zero
  • Figure 2: Bode magnitude plot for zero and low-pass pole; curves labeled "Bode" are the straight-line Bode plots
    Figure 2: Bode magnitude plot for zero and low-pass pole; curves labeled "Bode" are the straight-line Bode plots
  • Figure 3: Bode phase plot for zero and low-pass pole; curves labeled "Bode" are the straight-line Bode plots
    Figure 3: Bode phase plot for zero and low-pass pole; curves labeled "Bode" are the straight-line Bode plots
  • Figure 4: Bode magnitude plot for pole-zero combination; the location of the zero is ten times higher than in Figures 2 and 3; curves labeled "Bode" are the straight-line Bode plots
    Figure 4: Bode magnitude plot for pole-zero combination; the location of the zero is ten times higher than in Figures 2 and 3; curves labeled "Bode" are the straight-line Bode plots
  • Figure 5: Bode phase plot for pole-zero combination; the location of the zero is ten times higher than in Figures 2 and 3; curves labeled "Bode" are the straight-line Bode plots
    Figure 5: Bode phase plot for pole-zero combination; the location of the zero is ten times higher than in Figures 2 and 3; curves labeled "Bode" are the straight-line Bode plots

Gain margin and phase margin

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See also:Phase margin

Bode plots are used to assess the stability ofnegative-feedback amplifiers by finding the gain andphase margins of an amplifier. The notion of gain and phase margin is based upon the gain expression for a negative feedback amplifier given by

AFB=AOL1+βAOL,{\displaystyle A_{\text{FB}}={\frac {A_{\text{OL}}}{1+\beta A_{\text{OL}}}},}

whereAFB is the gain of the amplifier with feedback (theclosed-loop gain),β is thefeedback factor, andAOL is the gain without feedback (theopen-loop gain). The gainAOL is a complex function of frequency, with both magnitude and phase.[note 1] Examination of this relation shows the possibility of infinite gain (interpreted as instability) if the product βAOL = −1 (that is, the magnitude of βAOL is unity and its phase is −180°, the so-calledBarkhausen stability criterion). Bode plots are used to determine just how close an amplifier comes to satisfying this condition.

Key to this determination are two frequencies. The first, labeled here asf180, is the frequency where the open-loop gain flips sign. The second, labeled heref0 dB, is the frequency where the magnitude of the product |βAOL| = 1 = 0 dB. That is, frequencyf180 is determined by the condition

βAOL(f180)=|βAOL(f180)|=|βAOL|180,{\displaystyle \beta A_{\text{OL}}(f_{180})=-|\beta A_{\text{OL}}(f_{180})|=-|\beta A_{\text{OL}}|_{180},}

where vertical bars denote themagnitude of a complex number, and frequencyf0 dB is determined by the condition

|βAOL(f0 dB)|=1.{\displaystyle |\beta A_{\text{OL}}(f_{\text{0 dB}})|=1.}

One measure of proximity to instability is thegain margin. The Bode phase plot locates the frequency where the phase of βAOL reaches −180°, denoted here as frequencyf180. Using this frequency, the Bode magnitude plot finds the magnitude of βAOL. If |βAOL|180 ≥ 1, the amplifier is unstable, as mentioned. If |βAOL|180 < 1, instability does not occur, and the separation in dB of the magnitude of |βAOL|180 from |βAOL| = 1 is called thegain margin. Because a magnitude of 1 is 0 dB, the gain margin is simply one of the equivalent forms:20log10|βAOL|180=20log10|AOL|20log10β1{\displaystyle 20\log _{10}|\beta A_{\text{OL}}|_{180}=20\log _{10}|A_{\text{OL}}|-20\log _{10}\beta ^{-1}}.

Another equivalent measure of proximity to instability is thephase margin. The Bode magnitude plot locates the frequency where the magnitude of |βAOL| reaches unity, denoted here as frequencyf0 dB. Using this frequency, the Bode phase plot finds the phase of βAOL. If the phase of βAOL(f0 dB) > −180°, the instability condition cannot be met at any frequency (because its magnitude is going to be < 1 whenf =f180), and the distance of the phase atf0 dB in degrees above −180° is called thephase margin.

If a simpleyes orno on the stability issue is all that is needed, the amplifier is stable iff0 dB <f180. This criterion is sufficient to predict stability only for amplifiers satisfying some restrictions on their pole and zero positions (minimum phase systems). Although these restrictions usually are met, if they are not, then another method must be used, such as theNyquist plot.[6][7]Optimal gain and phase margins may be computed usingNevanlinna–Pick interpolation theory.[8]

Examples using Bode plots

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Figures 6 and 7 illustrate the gain behavior and terminology. For a three-pole amplifier, Figure 6 compares the Bode plot for the gain without feedback (theopen-loop gain)AOL with the gain with feedbackAFB (theclosed-loop gain). Seenegative feedback amplifier for more detail.

In this example,AOL = 100 dB at low frequencies, and 1 / β = 58 dB. At low frequencies,AFB ≈ 58 dB as well.

Because the open-loop gainAOL is plotted and not the product βAOL, the conditionAOL = 1 / β decidesf0 dB. The feedback gain at low frequencies and for largeAOL isAFB ≈ 1 / β (look at the formula for the feedback gain at the beginning of this section for the case of large gainAOL), so an equivalent way to findf0 dB is to look where the feedback gain intersects the open-loop gain. (Frequencyf0 dB is needed later to find the phase margin.)

Near this crossover of the two gains atf0 dB, the Barkhausen criteria are almost satisfied in this example, and the feedback amplifier exhibits a massive peak in gain (it would be infinity if βAOL = −1). Beyond the unity gain frequencyf0 dB, the open-loop gain is sufficiently small thatAFBAOL (examine the formula at the beginning of this section for the case of smallAOL).

Figure 7 shows the corresponding phase comparison: the phase of the feedback amplifier is nearly zero out to the frequencyf180 where the open-loop gain has a phase of −180°. In this vicinity, the phase of the feedback amplifier plunges abruptly downward to become almost the same as the phase of the open-loop amplifier. (Recall,AFBAOL for smallAOL.)

Comparing the labeled points in Figure 6 and Figure 7, it is seen that the unity gain frequencyf0 dB and the phase-flip frequencyf180 are very nearly equal in this amplifier,f180f0 dB ≈ 3.332 kHz, which means the gain margin and phase margin are nearly zero. The amplifier is borderline stable.

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 | βAOL | = 1 to lower frequency. In this example, 1 / β = 77 dB, and at low frequenciesAFB ≈ 77 dB as well.

Figure 8 shows the gain plot. From Figure 8, the intersection of 1 / β andAOL occurs atf0 dB = 1 kHz. Notice that the peak in the gainAFB nearf0 dB is almost gone.[note 2][9]

Figure 9 is the phase plot. Using the value off0 dB = 1 kHz found above from the magnitude plot of Figure 8, the open-loop phase atf0 dB is −135°, which is a phase margin of 45° above −180°.

Using Figure 9, for a phase of −180° the value off180 = 3.332 kHz (the same result as found earlier, of course[note 3]). The open-loop gain from Figure 8 atf180 is 58 dB, and 1 / β = 77 dB, so the gain margin is 19 dB.

Stability is not the sole criterion for amplifier response, and in many applications a more stringent demand than stability is goodstep response. As arule of thumb, good step response requires a phase margin of at least 45°, and often a margin of over 70° is advocated, particularly where component variation due to manufacturing tolerances is an issue.[9] See also the discussion of phase margin in thestep response article.

  • Examples
  • Figure 6: Gain of feedback amplifier AFB in dB and corresponding open-loop amplifier AOL. Parameter 1/β = 58 dB, and at low frequencies AFB ≈ 58 dB as well. The gain margin in this amplifier is nearly zero because | βAOL| = 1 occurs at almost f = f180°.
    Figure 6: Gain of feedback amplifierAFB in dB and corresponding open-loop amplifierAOL. Parameter 1/β = 58 dB, and at low frequenciesAFB ≈ 58 dB as well. The gain margin in this amplifier is nearly zero because | βAOL| = 1 occurs at almostf =f180°.
  • Figure 7: Phase of feedback amplifier °AFB in degrees and corresponding open-loop amplifier °AOL. The phase margin in this amplifier is nearly zero because the phase-flip occurs at almost the unity gain frequency f = f0 dB where | βAOL| = 1.
    Figure 7: Phase of feedback amplifier°AFB in degrees and corresponding open-loop amplifier°AOL. The phase margin in this amplifier is nearly zero because the phase-flip occurs at almost the unity gain frequencyf =f0 dB where | βAOL| = 1.
  • Figure 8: Gain of feedback amplifier AFB in dB and corresponding open-loop amplifier AOL. In this example, 1 / β = 77 dB. The gain margin in this amplifier is 19 dB.
    Figure 8: Gain of feedback amplifierAFB in dB and corresponding open-loop amplifierAOL. In this example, 1 / β = 77 dB. The gain margin in this amplifier is 19 dB.
  • Figure 9: Phase of feedback amplifier AFB in degrees and corresponding open-loop amplifier AOL. The phase margin in this amplifier is 45°.
    Figure 9: Phase of feedback amplifierAFB in degrees and corresponding open-loop amplifierAOL. The phase margin in this amplifier is 45°.

Bode plotter

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Figure 10: Amplitude diagram of a 10th-orderelectronic filter plotted using a Bode plotter

The Bode plotter is an electronic instrument resembling anoscilloscope, which produces a Bode diagram, or a graph, of a circuit's voltage gain or phase shift plotted againstfrequency in a feedback control system or a filter. An example of this is shown in Figure 10. It is extremely useful for analyzing and testing filters and the stability offeedback control systems, through the measurement of corner (cutoff) frequencies and gain and phase margins.

This is identical to the function performed by avector network analyzer, but the network analyzer is typically used at much higher frequencies.

For education and research purposes, plotting Bode diagrams for given transfer functions facilitates better understanding and getting faster results (see external links).

Related plots

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Main articles:Nyquist plot andNichols plot

Two related plots that display the same data in differentcoordinate systems are theNyquist plot and theNichols plot. These areparametric plots, with frequency as the input and magnitude and phase of the frequency response as the output. The Nyquist plot displays these inpolar coordinates, with magnitude mapping to radius and phase to argument (angle). The Nichols plot displays these in rectangular coordinates, on thelog scale.

See also

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Notes

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  1. ^Ordinarily, as frequency increases, the magnitude of the gain drops, and the phase becomes more negative, although these are only trends and may be reversed in particular frequency ranges. Unusual gain behavior can render the concepts of gain and phase margin inapplicable. Then other methods such as theNyquist plot have to be used to assess stability.
  2. ^The critical amount of feedback where the peak in the gainjust disappears altogether is themaximally flat orButterworth design.
  3. ^The frequency where the open-loop gain flips signf180 does not change with a change in feedback factor; it is a property of the open-loop gain. The value of the gain atf180 also does not change with a change in β. Therefore, we could use the previous values from Figures 6 and 7. However, for clarity the procedure is described using only Figures 8 and 9.

References

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  1. ^R. K. Rao Yarlagadda (2010).Analog and Digital Signals and Systems. Springer Science & Business Media. p. 243.ISBN 978-1-4419-0034-0.
  2. ^Van Valkenburg, M. E. University of Illinois at Urbana-Champaign, "In memoriam: Hendrik W. Bode (1905-1982)",IEEE Transactions on Automatic Control, Vol. AC-29, No 3., March 1984, pp. 193–194. Quote: "Something should be said about his name. To his colleagues at Bell Laboratories and the generations of engineers that have followed, the pronunciation is boh-dee. The Bode family preferred that the original Dutch be used as boh-dah."
  3. ^"Vertaling van postbode, NL>EN". mijnwoordenboek.nl. Retrieved2013-10-07.
  4. ^David A. MindellBetween Human and Machine: Feedback, Control, and Computing Before Cybernetics JHU Press, 2004,ISBN 0801880572, pp. 127–131.
  5. ^Skogestad, Sigurd; Postlewaite, Ian (2005).Multivariable Feedback Control. Chichester, West Sussex, England: John Wiley & Sons, Ltd.ISBN 0-470-01167-X.
  6. ^Thomas H. Lee (2004). "§14.6. Gain and Phase Margins as Stability Measures".The design of CMOS radio-frequency integrated circuits (2nd ed.). Cambridge UK: Cambridge University Press. pp. 451–453.ISBN 0-521-83539-9.
  7. ^William S. Levine (1996). "§10.1. Specifications of Control System".The control handbook: the electrical engineering handbook series (2nd ed.). Boca Raton FL: CRC Press/IEEE Press. p. 163.ISBN 0-8493-8570-9.
  8. ^Allen Tannenbaum (February 1981).Invariance and Systems Theory: Algebraic and Geometric Aspects. New York, NY: Springer-Verlag.ISBN 9783540105657.
  9. ^abWilly M C Sansen (2006).Analog design essentials. Dordrecht, The Netherlands: Springer. pp. 157–163.ISBN 0-387-25746-2.

External links

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