ECE 3355 Electronics - University of Houston

Dave Shattuck University of Houston University of Houston ECE 3355 Electronics Lecture Notes Set 3 Version 31 Frequency Response and Bode Plots Dr. Dave Shattuck Dept. of ECE, Univ. of Houston Dave Shattuck University of Houston University of Houston Amplifier Frequency Response We will cover material from Section 1.2 (pages 9-12), Section 1.6 (pages 3343), and Appendix F (on website) from the 7th Edition of the Sedra and Smith

text. It may also be useful for you to consult the Nilsson & Riedel Electric Circuits text. The material is from Appendix E of the 10th Edition. Dave Shattuck University of Houston University of Houston Fourier's Theorem Fourier's Theorem says that any physically realizable signal can be represented by, and is equivalent to, a summation of sinusoids of different frequencies, amplitudes and phases. Any physically realizable signal translates to any voltage or current, as a function of time, that we can produce or measure.

Repeat after me: 4-E-A. Dave Shattuck University of Houston University of Houston Fourier's Theorem Fourier's Theorem has profound implications, and represents a significant paradigm shift for electrical engineering. We can think of any signal in terms of its frequency components, which are the amplitudes of the sine waves at that frequency. We can find of the response of an amplifier to sinusoids, and predict the response to any signal. Dave Shattuck University of Houston

University of Houston Fourier's Theorem Fourier's Theorem has profound implications, and represents a significant paradigm shift for electrical engineering. We can think of any signal in terms of its frequency components, which are the amplitudes of the sine waves at that frequency. We can find of the response of an amplifier to sinusoids, and predict the response to any signal. Whats a paradigm? Dave Shattuck University of Houston University of Houston What are paradigms?

About 20 cents. Get it? Pair a dimes? Okay, so it is not very funny Dave Shattuck University of Houston University of Houston Fourier's Theorem Fourier's Theorem has profound implications, and represents a significant paradigm shift for electrical engineering. We can think of any signal in terms of its frequency components, which are the amplitudes of the sine waves at that frequency. We can find of the

response of an amplifier to sinusoids, and predict the response to any signal. Whats a paradigm? A paradigm is a way of thinking about something. A paradigm shift is a change in a way of thinking about something. Dave Shattuck University of Houston University of Houston Fourier's Theorem Fourier's Theorem has profound implications, and represents a significant paradigm shift for electrical engineering. We can think of any signal in terms of its frequency components, which are the amplitudes of the sine waves at that frequency. We can find of the response of an amplifier to sinusoids, and predict the response to any signal.

All of this is made more important by the power of phasor analysis, which makes the analysis of sinusoids relatively easy and quick. Dave Shattuck University of Houston University of Houston Frequency Response Notation To agree with the text, we will use the notation of uppercase variables with lowercase subscripts for phasors. I will not use bold face for the variables when I am writing by hand, but will use it for the text in these notes, to agree with the textbook. The phasor of va will be Va. Dave Shattuck University of Houston

University of Houston Frequency Spectrum A frequency spectrum of a signal is the plot of the amplitude of each frequency component, plotted vs frequency. We can also plot the phase vs frequency. This is often useful, but in other situations, it can be ignored. It depends. We can also plot the response of a circuit to signals versus frequency, and this will be our emphasis in this course. Let's define some more terms. Dave Shattuck University of Houston University of Houston Transfer Function

The Phoenician says: Transfer Function = the ratio of the output phasor to the input phasor for a circuit. This is also called the frequency response of the circuit. Vo ( ) T ( ) H ( ) Vi ( ) Dave Shattuck University of Houston University of Houston Transfer Function Note that H() (the notation used in the Nilsson book) is a ratio of two complex quantities, so must be complex as well. Thus, H() must have a magnitude and a phase.

By the rules of complex arithmetic, we have these relationships. We will find it useful to plot |H()| vs , and also, but less often, useful to plot H() vs . Vo ( ) H ( ) Vi ( ) Vo ( ) H( ) Vi ( ) H( ) Vo ( ) Vi ( ) Dave Shattuck University of Houston University of Houston

Transfer Function Transfer Function = the ratio of the output phasor to the input phasor for a circuit. This is also called the frequency response of the circuit. Lets consider a plot of the magnitude of the frequency response as a function of . Vo ( ) H ( ) Vi ( ) Dave Shattuck University of Houston University of Houston Passband and Bandwidth We often call the relatively flat area where the circuit or amplifier is usually used, the passband. The value in this area is called the

passband response, or the passband gain. The range of where this passband is located is called the bandwidth. Vo ( ) H ( ) Vi ( ) Dave Shattuck University of Houston University of Houston Passband and Bandwidth We often call the relatively flat area where the circuit or amplifier is usually used, the passband. The value in this area is called the passband response, or the passband gain. The range of where this passband is located is called the bandwidth. Each of these values can be defined

quantitatively. We often plot |H()| in dB. Then, we get the 3dB bandwidth, which is the range of where the response is constant within 3dB of the passband response. Dave Shattuck University of Houston University of Houston 3[dB] Bandwidth Stated explicitly, we identify a value which represents the gain in the passband. We express this gain in dB, and then subtract 3dB from that value. The place where the response intersects this value (passband gain - 3dB) at the top of the passband, we call H. The place where the response intersects this value (passband gain - 3dB) at the bottom of the

passband, we call L. The difference between these two values is the 3dB bandwidth, or BW3dB H L Dave Shattuck University of Houston University of Houston Filters We often use circuits with responses that we categorize as a filter. This is where we have a response as a function of frequency with a specific characteristic. lowpass filter - passes low frequencies, and attenuates higher frequencies. highpass filter - passes high frequencies, and

attenuates lower frequencies. bandpass filter - attenuates high frequencies, and attenuates lower frequencies. Dave Shattuck University of Houston University of Houston Filter Example But, how do we get these things? Let's do an example problem. I will pick a lowpass RC circuit. a) Find the transfer function, H(). b) Find the amplitude of the transfer function. c) Find the phase of the transfer function. d) Describe the behavior of each as 0, and .

Dave Shattuck University of Houston University of Houston Filter Example But, how do we get these things? Let's do an example problem. I will pick a lowpass RC circuit. a) Find the transfer function, H(). Solution: Apply the voltage divider rule (in the phasor domain), and we get: 1 V0 1 j C H ( ) . 1 Vs

1 j CR R j C Dave Shattuck University of Houston University of Houston Filter Example But, how do we get these things? Let's do an example problem. I will pick a lowpass RC circuit. b) Find the amplitude of the transfer function. H ( )

1 2 1 CR . 2 Dave Shattuck University of Houston University of Houston Filter Example But, how do we get these things? Let's do an example problem. I will pick a lowpass RC circuit. c) Find the phase of the transfer function.

H ( ) 0 arctan(CR ) arctan(CR ). Dave Shattuck University of Houston University of Houston Filter Example But, how do we get these things? Let's do an example problem. I will pick a lowpass RC circuit. d) Describe the behavior of each as 0, and . Actually, it is easier to look at this part by going back to the solution in a). Specifically, for small , then (1+jCR) is approximately just 1, and H ( ) 1 and for large , then (1+jCR) is approximately just jCR, and

1 H ( ) . jCR Dave Shattuck University of Houston University of Houston Filter Example Note that we have one behavior for the real part of the denominator dominant, and another for the imaginary part dominant. In other words, we have one behavior for CR >> 1, and another for CR << 1. The crossover point is where

CR = 1, or where = 1 / CR. We call this the breakpoint frequency, for reasons which will become obvious later. Dave Shattuck University of Houston University of Houston Filter Example We think of having three different behaviors corresponding to these 3 cases. First, for >> 1 / CR, |H()| = 1/wCR, and H() = -90. Then, for << 1 / CR, |H()| = 1, and H() = 0. Finally, for = 1 / CR,

1 H( ) 3dB 2 and, H() = -45. Dave Shattuck University of Houston University of Houston Bode Plots We now consider Bode Plots. With Bode Plots, we plot the magnitude in dB vs the log of or f, and plot the phase (on a linear scale) vs the log of or f. Dave Shattuck University of Houston

University of Houston Bode Plots We now consider Bode Plots. With Bode Plots, we plot the magnitude in dB vs the log of or f, and plot the phase (on a linear scale) vs the log of or f. Why logarithmic scales? Answer: Because we think logarithmically. No, really, why do we use logarithmic scales? Answer: Because we think logarithmically. Prove this using dollar bills. If this proof is not convincing, I don't think I can prove it to you. Dave Shattuck University of Houston University of Houston

Bode Plots We now consider Bode Plots. With Bode Plots, we plot the magnitude in dB vs the log of or f, and plot the phase (on a linear scale) vs the log of or f. Now, we can see why Bode plots are so useful. Bode plots tell us everything we need to know about the response of an amplifier, and gives it to us in the most useful possible way, the way that reflects best the values that we have. In the material that follows, we will show a way of plotting them quickly and easily. Dave Shattuck University of Houston University of Houston Bode Plots

We now consider Bode Plots. With Bode Plots, we plot the magnitude in dB vs the log of or f, and plot the phase (on a linear scale) vs the log of or f. Tells us everything. Most useful form. Easy to plot. This is nerd heaven. I know I love Bode Plots. Maybe you will, too. See for yourself. Straight-Line Approximations to Bode Plots Dave Shattuck University of Houston University of Houston Bode Plots are plots of the magnitude in dB

vs the log of or f, and the phase (on a linear scale) vs the log of or f. Bode plots have become associated with the idea of the straight line approximations to these same plots. Note again: The straight line approximations are not the most important reason for using logarithmic plots, but they help make them even more useful. Dave Shattuck University of Houston University of Houston Transfer Function Form If we restrict ourselves to the case of real valued poles and zeroes, then we can obtain the transfer function as a ratio of the product of terms, as

K j z1 j z2 ... H ( ) j p1 j p2 ... For this course, the z's and p's will be real. Dave Shattuck University of Houston University of Houston Breakpoints These values correspond to frequencies where the dominant part of the term is changing: from not frequency dependent to frequency dependent. These are values of frequency where the behavior of that term changes. We will call these values breakpoints.

K j z1 j z2 ... H ( ) j p1 j p2 ... Dave Shattuck University of Houston University of Houston Behavior with Frequency These values correspond to frequencies where the dominant part of the term is changing from not frequency dependent to frequency dependent. Note that for: >> zn, (j + zn) will increase linearly with , and thus H() will increase linearly with . >> pn, (j + pn) will increase linearly with , and thus H() will decrease linearly with .

K j z1 j z2 ... H ( ) j p1 j p2 ... Dave Shattuck University of Houston University of Houston Transferance of Dominance These values correspond to frequencies where the dominant part of the term is changing from not frequency dependent to frequency dependent. We would like to find a way to get these breakpoints quickly. We will sometimes use a mathematical technique: Let js. Then, we have K s z1 s z 2 ...

H (s) s p1 s p2 ... Poles and Zeroes Dave Shattuck University of Houston University of Houston In this situation, the zn's are zeroes, and pn's are poles. Actually, the zns and pns are the additive inverses of the zeroes and poles. In this course, the sign does not matter. Therefore, we can use existing mathematic

techniques to find the zeroes and poles, and thus find the breakpoints. K s z1 s z 2 ... H (s) s p1 s p2 ... Dave Shattuck University of Houston University of Houston Poles and Zeroes For our simple cases, these zn's and pn's will be real values. Strictly speaking, they are not really poles and zeroes of H(), since (j + a) is not really zero for any real value of a. However, we are engineers, and are not interested in speaking strictly. We want useful approximations.

K j z1 j z2 ... H ( ) j p1 j p2 ... Dave Shattuck University of Houston University of Houston Poles and Zeroes For our simple cases, these zn's and pn's will be real values. Strictly speaking, they are not really poles and zeroes of H(), since (j + a) is not really zero for any real value of a. For us, poles are frequency values where the real and imaginary parts of a term in the denominator are equal.

K j z1 j z2 ... H ( ) j p1 j p2 ... Dave Shattuck University of Houston University of Houston Poles and Zeroes For our simple cases, these zn's and pn's will be real values. Strictly speaking, they are not really poles and zeroes of H(), since (j + a) is not really zero for any real value of a. For us, zeroes are frequency values where the real and imaginary parts of a term in the numerator are equal. K j z1 j z2 ...

H ( ) j p1 j p2 ... Dave Shattuck University of Houston University of Houston Poles and Zeroes In other courses, we will worry about the signs of the poles and zeroes. For the purposes of this course, we will not worry about these signs. We will have plenty to worry about. We will limit the cases we consider to situations where the sign doesn't matter. Worry about signs! K j z1 j z2 ... H ( ) j p1 j p2 ...

Dave Shattuck University of Houston University of Houston Straight Line Approximation Rules Our approach to plotting Bode plots using the straight line approximations: 1. Obtain the transfer function H(). 2. Find the poles and zeroes of H(). Poles are frequency values where the real and imaginary parts of a term in the denominator are equal. Zeroes are frequency values where the real and imaginary parts of a term in the numerator are equal. Dave Shattuck

University of Houston University of Houston Straight Line Approximation Rules 3. Plot the Magnitude Plot A. Evaluate |H()| at some . Pick an easy spot. B. Plot the straight line approximation. i. At poles, the slope decreases by 20[dB/decade] as you move to the right. ii. At zeroes, the slope increases by 20[dB/ decade] as you move to the right. Dave Shattuck University of Houston University of Houston

Straight Line Approximation Rules 3. C. (optional) Mark off some corrections to these straight lines, and plot more accurate curves. i. At poles, label a point 3[dB] below the straight line approximation. ii. At zeroes, label a point 3[dB] above the straight line approximation. iii. Draw a smooth curve through these points using the straight lines as asymptotes. Dave Shattuck University of Houston University of Houston Straight Line Approximation Rules

3. D. For multiple poles and zeroes, increase the effects proportionately. i. If you have nz zeroes, the slope increases by nz x 20[dB/dec], and the correction at the breakpoint is nz x 3[dB]. ii. If you have np poles, the slope decreases by np x 20[dB/dec], and the correction at the breakpoint is np x 3[dB]. Dave Shattuck University of Houston University of Houston Straight Line Approximation Rules 4. Plot the Phase Plot

A. Evaluate H() at some . Pick an easy spot. B. Plot the straight line approximation. i. At p/10, the slope decreases by 45[/decade] as you move to the right, for 2 decades only (until 10p). ii. At z/10, the slope increases by 45[/decade] as you move to the right, for 2 decades only (until 10z). Dave Shattuck University of Houston University of Houston Straight Line Approximation Rules 4. C. (optional) Mark off some corrections to these straight lines, and plot more accurate curves.

i. At p/10, label a point 5.7 below the straight line approximation. ii. At 10p, label a point 5.7 above the straight line approximation. iii. At z/10, label a point 5.7 above the straight line approximation. iv. At 10z, label a point 5.7 below the straight line approximation. v. Draw a smooth curve through these points using the straight lines as asymptotes. Dave Shattuck University of Houston University of Houston Straight Line Approximation Rules 4. D. For multiple poles and zeroes, increase the effects proportionately.

i. If you have nz zeroes, the slope increases by nz x 45[/dec], and the correction at the breakpoints is nz x 5.7. ii. If you have np poles, the slope decreases by np x 45[/dec], and the correction at the breakpoints is np x 5.7. Dave Shattuck University of Houston University of Houston Sample Plots The following plots are a sample Bode plot. The transfer function for these plots is T( ) 10 7

j j 1j 10 4 This transfer function has one zero, at 0, and two poles, one at 1 and one at 10,000. (The units are not shown, since this is an arbitrary example. In a real transfer function, the units would be indicated here and on all the plots that follow.) The magnitude plot, in dB, is given in the next slide. Note that the straight line approximations, also drawn, approach the actual curve assymptotically away from the breakpoints. Dave Shattuck University of Houston

Sample Plots University of Houston Magnitude in dB Straight line approx. Magnitude Plot 60 50 40 30 20 10 0 -10 0.001 0.01

0.1 1 10 100 1000 Frequency (log scale) 10000 100000 1000000 Dave Shattuck University of Houston University of Houston

Sample Plots The following plots are a sample Bode plot. The transfer function for these plots is T( ) 10 7 j j 1j 10 4 This transfer function has one zero, at 0, and two poles, one at 1 and one at 10,000. Now, if we plot the error between the actual plot and the straight-line approximation, we get the plot in

the following slide. Dave Shattuck University of Houston Sample Plots University of Houston 3.50 Error in Straight Line Approximation in dB Magnitude Plot 3.00 2.50 2.00 1.50 1.00 0.50 0.00

0.001 0.01 0.1 1 10 100 1000 Frequency (log scale) 104 105 106 107 Dave Shattuck

University of Houston University of Houston Sample Plots The following plots are a sample Bode plot. The transfer function for these plots is T( ) 10 7 j j 1j 10 4

This transfer function has one zero, at 0, and two poles, one at 1 and one at 10,000. Now, if we plot the phase plot, we get the plot in the following slide. Dave Shattuck University of Houston Sample Plots University of Houston Phase Plot in Degrees Phase (in degrees) Straight line approx. 100 80 60 40

20 0 -20 -40 -60 -80 -100 10-2 10-1 100 101 102 103 104 105 Frequency (log scale) 106 107 Dave Shattuck

University of Houston University of Houston Sample Plots The following plots are a sample Bode plot. The transfer function for these plots is T( ) 10 7 j j 1j 10 4

This transfer function has one zero, at 0, and two poles, one at 1 and one at 10,000. Now, if we plot the error between the actual plot and the straight-line approximation, we get the plot in the following slide. Dave Shattuck University of Houston University of Houston 6 Sample Plots Error in Straight Line Approximation Phase Plot, in degrees 4 2

0 -2 -4 -6 0.01 0.1 1 10 100 1000 104 105 Frequency (log scale) 106 107 Dave Shattuck University of Houston

University of Houston Errors in Straight-Line Approximations The largest errors occur where the straight line approximation has a change in slope. In the magnitude plots, this happens at the locations of the poles and zeroes. In the phase plots, this happens at both a decade above and a decade below the locations of the poles and zeroes. Dave Shattuck University of Houston University of Houston Examples If you want to look at this data more carefully, it is

available in a Microsoft Excel spreadsheet, called Bode_plot_example, which should be available on the network. Lets do an example problem. Work on problem using the overhead projector, showing how semilog graph paper works. Dave Shattuck University of Houston University of Houston Dave Shattuck University of Houston University of Houston

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