# CH10. Feedback :::info **Disclaimer** Cases involving BJTs are temporarily omitted, I might work on them someday if I have time. Also, if you spot any error, please contact me via my email: bigbeeismusic@gmail.com ::: ## 10.1 The General Feedback Structure ### 10.1.1 Signal-Flow Diagram ![截圖 2025-01-09 下午5.45.38](https://hackmd.io/_uploads/SyuOiMpUye.png) :::warning ++Definition++. **Open-loop gain**: $A=\frac{x_o}{x_i}$ **Feedback factor**: $\beta=\frac{x_f}{x_o}$ $x_i=x_s-x_f$ ::: ### 10.1.2 The Closed-Loop Gain $A_f\equiv\frac{x_o}{x_s}=\frac{A}{1+A\beta}$ ($A\beta$: **loop gain** / $(1+A\beta)$: **amount of feedback**) When $A\beta\gg 1$, $A_f\simeq\frac{1}{\beta}\Rightarrow A_f|_{\text{ideal}}=\frac{1}{\beta}$ $\Rightarrow A_f=A_f|_{\text{ideal}}\frac{1}{1+(1/A\beta)}$ :::info ++Note++. We can rewrite the expression of signals: $x_f=\frac{A\beta}{1+A\beta}x_s$, $x_i=\frac{1}{1+A\beta}x_s$ $x_i$ is sometimes referred to as the **error signal**. ::: ### 10.1.3 The Loop Gain :::info ++Observation++. - $A\beta>0\Leftrightarrow$ negative feedback. - $A\beta\nearrow\Rightarrow A_f\rightarrow A_f|_{\text{ideal}}$ ::: **find the loop gain** ![截圖 2025-01-09 下午6.07.43](https://hackmd.io/_uploads/rknGxQT8kx.png) 1. Set $x_s=0$. 2. Break the feedback loop. 3. Apply $x_t$ at where the break is and determine the return signal $x_r$, we have $x_r=-A\beta x_t\Rightarrow A\beta=-\frac{x_r}{x_t}$ ### 10.1.4 The Ideal Case of Infinite Open-Loop Gain $A$ ![截圖 2025-01-09 下午6.14.12](https://hackmd.io/_uploads/rJuqb7681e.png) $\Rightarrow x_i=0$, $x_f=x_s$ $\Rightarrow x_o=\frac{1}{\beta}x_s$ $\Rightarrow A_f|_{\text{ideal}}=\frac{x_o}{x_s}$ ## 10.2 Some Properties of Negative Feedback ### 10.2.1 Gain Desensitivity $dA_f=\frac{dA}{(1+A\beta)^2}\Rightarrow\frac{dA_f}{A_f}=\frac{1}{1+A\beta}\frac{dA}{A}$ ($(1+A\beta)$: **desensitivity factor**) ### 10.2.2 Bandwidth Extension Consider $A(s)=\frac{A_M}{1+s/\omega_H}$ $\Rightarrow A_f(s)=\frac{A(s)}{1+\beta A(s)}=\frac{A_M/(1+s/\omega_H)}{1+\beta[A_M/(1+s/\omega_H)]}=\frac{A_M/(1+A_M\beta)}{1+s/[\omega_H(1+A_M\beta)]}$ $\Rightarrow \omega_{Hf}=\omega_H(1+A_M\beta)$ ![截圖 2025-01-09 下午6.28.44](https://hackmd.io/_uploads/Sk9xBQaU1g.png) ### 10.2.3 Reduction in Nonlinear Distortion ![截圖 2025-01-09 下午6.31.31](https://hackmd.io/_uploads/r1mcHm6Lkl.png) ((a): without feedback, (b): with feedback) ## 10.3 The Feedback Voltage Amplifier ### 10.3.1 The Series-Shunt Feedback Topology ![截圖 2025-01-09 下午6.35.36](https://hackmd.io/_uploads/r1_tUXpLJg.png) (voltage-mixing, voltage-sampling) ### 10.3.2 Examples of Series-Shunt Feedback Amplifiers ![截圖 2025-01-14 下午5.27.39](https://hackmd.io/_uploads/By0fRomPkx.png) ### 10.3.3 Analysis of the Feedback Voltage Amplifier #### Step 1: Determine $\beta$ and $A_f|_{\text{ideal}}$ ![截圖 2025-01-14 下午5.47.06](https://hackmd.io/_uploads/Byx3G2XPJe.png) First assume that $A=\infty$, find $A_f|_{\text{ideal}}=\frac{1}{\beta}=\frac{V_o}{V_f}=\frac{V_o}{V_s}$. #### Step 2: Determine the Loop Gain $A\beta$ ![截圖 2025-01-14 下午5.55.01](https://hackmd.io/_uploads/B1tYV37vke.png) Break the feedback loop and apply a test voltage $V_t$ and connect another break of the loop with impedance $Z_t$ (whose value is equal to the impeadance looking into $XX'$), we have $A\beta=-\frac{V_r}{V_t}$ #### Step 3: Determine the Closed-Loop Gain $A_f$ Combine two result, we have $A_f=\frac{A}{1+A\beta}$ ## 10.4 Systematic Analysis of Feedback Voltage Amplifiers ### 10.4.1 The Ideal Case ![截圖 2025-01-14 下午6.03.33](https://hackmd.io/_uploads/r19tI2QDyg.png) (In (a), the $\beta$ circuit does **not** load the $A$ circuit) $\Rightarrow A_f\equiv\frac{V_o}{V_s}=\frac{A}{1+A\beta}$ **Find $R_{if}$** $V_{i}=\frac{V_{s}}{1+A\beta}\Rightarrow I_i=\frac{V_i}{R_i}=\frac{V_s}{(1+A\beta)R_i}\Rightarrow R_{if}\equiv\frac{V_s}{I_i}=(1+A\beta)R_i$ **Find $R_{of}$** - Let $V_s=0$, apply $V_x$ at output terminal $I_x=\frac{V_x-AV_i}{R_o}$, $V_i=-V_f=-\beta V_x\Rightarrow R_{of}=\frac{V_x}{I_x}=\frac{R_o}{1+A\beta}$ ### 10.4.2 The Practical Case ![截圖 2025-01-14 晚上10.08.11](https://hackmd.io/_uploads/HJ0AkeEDkx.png) **Interior Structure** ![截圖 2025-01-14 晚上10.09.04](https://hackmd.io/_uploads/Sk5zee4Pyx.png) ($R_s$: source resistance, $R_L$: load resistance, $R_{11}$&$R_{22}$: resistance due to the loading effect of the feedback network, see the following figure) ![截圖 2025-01-14 晚上10.11.41](https://hackmd.io/_uploads/Sy91Wl4PJx.png) **Find $\beta$** ![截圖 2025-01-14 晚上10.27.55](https://hackmd.io/_uploads/BJ-2El4DJx.png) $\beta\equiv\left.\frac{V_f}{V_o}\right|_{I_1=0}$ **Find Loop Gain $A\beta$** ![截圖 2025-01-14 晚上10.30.45](https://hackmd.io/_uploads/ByDQSxED1x.png) $A=\frac{V_o}{V_i}$ Closed loop gain $\Rightarrow A_f\equiv\frac{V_o}{V_s}=\frac{A}{1+A\beta}$ **Find Input/Output Resistance $R_{if}$/$R_{of}$** First find $R_i$/$R_o$ (see above figure) $\Rightarrow R_{if}=(1+A\beta)R_i$, $R_{of}=R_o/(1+A\beta)$ :::info ++Note++. Because the $R_{if}$/$R_{of}$ we calculated above have in fact included $R_s$/$R_L$, we have to subtract them when representing the actual $R_{in}$/$R_{out}$: $R_{in}=R_{if}-R_{s}$ $R_{out}=1/\left(\frac{1}{R_{of}}-\frac{1}{R_{L}}\right)$ ::: ## 10.5 Other Feedback-Amplifier Types ### 10.5.1 Basic Principles 1. **Sensing**: The feedback network must sample the output signal of interest. - If $V_o$ is of interested, the feedback network is connected in parallel (shunt). - If $I_o$ is of interested, the feedback network is connected in series. ![截圖 2025-01-14 晚上10.54.20](https://hackmd.io/_uploads/B1G29g4Pyx.png) 2. **Mixing**: - If the input signal to be amplified is a voltage, $V_f$ is connected in series with the input signal source $V_s$. - If the signal to be amplified is a current, the feedback current signal $I_f$ is connected in parallel (shunt) with the input signal source $I_s$. ![截圖 2025-01-14 晚上10.56.04](https://hackmd.io/_uploads/r1Omil4wJe.png) 3. **Feedback topology**: ![截圖 2025-01-14 晚上10.59.57](https://hackmd.io/_uploads/rJ6ehlVw1e.png) 4. **Input and output resistance**: The increase or decrease of the input or output resistance depends solely on the type of connection. - Series connection always increases the resistance by the amount of feedback, $(1+A\beta)$. - Parallel (shunt) connection always decreases the resistance by the amount of feedback, $(1+A\beta)$. 5. **Dimensions of $A$, $\beta$, $A\beta$, and $A_f$**: - Depending on the amplifier type, $A$, $\beta$ and $A_f$ have the dimensions of V/V, A/A, V/A, or A/V. However, - $A\beta$ is always dimensionless. 6. **Determining $\beta$ and $A_f|_{\text{ideal}}$**: To determine $\beta$, set $A=\infty$. - For the voltage (series) mixing case, $V_i=0$ and hence $I_i=0$, and $\beta$ is found as the ratio of the open-circuit voltage $V_f$ to the output quantity being sensed. - For the case of current (shunt) mixing, $I_i=0$ and hence $V_i=0$, and $\beta$ is found as the ratio of the short-circuit current $I_f$ to the output quantity being sensed. - The ideal value of the closed-loop gain is $A_f|_{\text{ideal}}=1/\beta$. 7. **Analysis using the loop gain**: $A_f=\frac{A}{1+A\beta}$. 8. **Find input and output resistance**: described later. ### 10.5.2 The Feedback Transconductance Amplifier (Series-Series) **Ideal Structure** ![截圖 2025-01-14 晚上11.20.02](https://hackmd.io/_uploads/SJOplW4vkl.png) **Equivalent Circuit** ![截圖 2025-01-14 晚上11.21.13](https://hackmd.io/_uploads/SyYbZ-4Dke.png) **Formulas** $A_f=\frac{I_o}{V_s}=\frac{A}{1+A\beta}$, $A_f|_{\text{ideal}}=\frac{1}{\beta}$ $R_{if}=(1+A\beta)R_i$, $R_{of}=(1+A\beta)R_o$ **General Structure** ![截圖 2025-01-14 晚上11.25.20](https://hackmd.io/_uploads/r1_ZfWNP1l.png) **Finding the $A$ circuit and $\beta$** ![截圖 2025-01-14 晚上11.27.08](https://hackmd.io/_uploads/H1n1XWEwJl.png) ![截圖 2025-01-14 晚上11.27.17](https://hackmd.io/_uploads/ry31mWEvkl.png) **Gain, Input, and Output Resistance** Use formula mentioned to find $A_f|_{\text{ideal}}$, $A_f$, $R_{if}$ and $R_{of}$. $\Rightarrow R_{in}=R_{if}-R_s$, $R_{out}=R_{of}-R_L$ ### 10.5.3 The Feedback Transresistance Amplifier (Shunt-Shunt) **Ideal Structure** ![截圖 2025-01-14 晚上11.34.43](https://hackmd.io/_uploads/B1EN4-ND1x.png) **Equivalent Circuit** ![截圖 2025-01-14 晚上11.34.52](https://hackmd.io/_uploads/r1IHVWEvkg.png) **Formulas** $A_f=\frac{V_o}{I_s}=\frac{A}{1+A\beta}$, $A_f|_{\text{ideal}}=\frac{1}{\beta}$ $R_{if}=R_i/(1+A\beta)$, $R_{of}=R_o/(1+A\beta)$ **General Structure** ![截圖 2025-01-14 晚上11.35.58](https://hackmd.io/_uploads/SygZiEZ4DJg.png) **Finding the $A$ circuit and $\beta$** ![截圖 2025-01-14 晚上11.36.08](https://hackmd.io/_uploads/SJvY4-VPke.png) ![截圖 2025-01-14 晚上11.36.21](https://hackmd.io/_uploads/BJx54ZNDkx.png) **Gain, Input, and Output Resistance** Use formula mentioned to find $A_f|_{\text{ideal}}$, $A_f$, $R_{if}$ and $R_{of}$. $\Rightarrow R_{in}=1/\left(\frac{1}{R_{if}}-\frac{1}{R_s}\right)$, $R_{out}=1/\left(\frac{1}{R_{of}}-\frac{1}{R_L}\right)$ ### 10.5.4 The Feedback Current Amplifier (Shunt-Series) **Ideal Structure** ![截圖 2025-01-14 晚上11.38.44](https://hackmd.io/_uploads/ryHHHZEwJe.png) **Equivalent Circuit** ![截圖 2025-01-14 晚上11.38.53](https://hackmd.io/_uploads/S1yLSZ4PJl.png) **Formulas** $A_f=\frac{I_o}{I_s}=\frac{A}{1+A\beta}$, $A_f|_{\text{ideal}}=\frac{1}{\beta}$ $R_{if}=R_i/(1+A\beta)$, $R_{of}=(1+A\beta)R_o$ **General Structure** ![截圖 2025-01-14 晚上11.39.06](https://hackmd.io/_uploads/HkxUS-EP1l.png) **Finding the $A$ circuit and $\beta$** ![截圖 2025-01-14 晚上11.39.15](https://hackmd.io/_uploads/rkgLSZEDJe.png) ![截圖 2025-01-14 晚上11.39.27](https://hackmd.io/_uploads/rkkLr-NDkl.png) **Gain, Input, and Output Resistance** Use formula mentioned to find $A_f|_{\text{ideal}}$, $A_f$, $R_{if}$ and $R_{of}$. $\Rightarrow R_{in}=1/\left(\frac{1}{R_{if}}-\frac{1}{R_s}\right)$, $R_{out}=R_{of}-R_L$ ## 10.6 Summary of the Feedback-Analysis Method 1. Always begin by finding $A_f|_{\text{ideal}}$. 2. Sketch the two-port feedback circuit and determine its loading effects $R_{11}$ and $R_{22}$. 3. Sketch the A circuit and analyze it to determine $A$, $R_i$, and $R_o$. 4. Calculate $A\beta$ and the amount of feedback $(1+A\beta)$. 5. Use formulas to determine $A_f$, $R_{if}$ and $R_{of}$. The difference between $A_f$ and $A_f|_{\text{ideal}}$ should be approximately $(100/A\beta)\%$. ## 10.7 The Stability Problem **Transfer function**: $A_f(s)=\frac{A(s)}{1+A(s)\beta(s)}$ Assume that dc gain of the amplifier is $A_0$ and at low frequency, $\beta(s)$ is constant. Consider $A(j\omega)\beta(j\omega)=|A(j\omega)\beta(j\omega)|e^{j\phi(\omega)}$, if $\phi(\omega)\to 180^{\circ}$, the feedback would be **positive**. - If $|A(j\omega_{180})\beta(j\omega_{180})|<1$, then $A_f>A$ (the amp is still stable, though). - If $|A(j\omega_{180})\beta(j\omega_{180})|=1$, then $A_f=\infty\Rightarrow$ **oscillator**. - If $|A(j\omega_{180})\beta(j\omega_{180})|>1$, then the circuit will oscillate, amplitude will increase until reaching nonlinearity. ## 10.8 Effect of Feedback on the Amplifier Poles ### 10.8.1 Stability and Pole Location :::success ++Recall++. (in "Signals and Systems" course) For an LTI system to be stable, the ROC of its transfer function should includes the entire $j\omega$-axis. Furthermore, for a causal and stable system, all poles should lie in the **left half of the s plane**. ::: ![截圖 2025-01-17 下午5.34.51](https://hackmd.io/_uploads/rkHU4jPD1l.png) ### 10.8.2 Poles of the Feedback Amplifier $\Rightarrow 1+A(s)\beta(s)=0$ (the **characteristic equation**) :::info ++Note++. From now on, we assume that the open loop amplifier has real poles and no finite zeros $\Rightarrow$ **no pole-zero cancellation**. We also assume that $\beta$ is independent of frequency. ::: ### 10.8.3 Amplifiers with a Single-Pole Response $A(s)=\frac{A_0}{1+s/\omega_P}\Rightarrow A_f(s)=\frac{A_0/(1+A_0\beta)}{1+s/\omega_P(1+A_0\beta)}$ $\omega_{Pf}=\omega_P(1+A_0\beta)$ ![截圖 2025-01-17 下午5.43.31](https://hackmd.io/_uploads/BJX2wsDvyg.png) :::info ++Observation++. At high frequency, $A_f(s)\simeq\frac{A_0\omega_P}{s}\simeq A(s)$ ::: The amplifier is said to be **unconditionally stable** because it is stable regardless of the value of $\beta$ (one can observe that by noticing that the maximum phase shift for a single-pole response is $90^{\circ}$ and can never reach $180^{\circ}$). ### 10.8.4 Amplifiers with a Two-Pole Response $A(s)=\frac{A_0}{(1+s/\omega_{P1})(1+s/\omega_{P2})}$ $1+A(s)\beta=0\Rightarrow s^2+s(\omega_{P1}+\omega_{P2})+(1+A_0\beta)\omega_{P1}\omega_{P2}=0$ $s=-\frac{1}{2}(\omega_{P1}+\omega_{P2})\pm\frac{1}{2}\sqrt{(\omega_{P1}+\omega_{P2})^2-4(1+A_0\beta)\omega_{P1}\omega_{P2}}$ ![截圖 2025-01-17 下午5.58.18](https://hackmd.io/_uploads/rJYAFivwkg.png) (The **root-locus diagram**, the arrows indicates how poles move as the $\beta$ increases.) The amplifier is also **unconditionally stable**. :::success ++Recall++. The characteristic equation of a second-order network can be written as $1+\frac{1}{Q}\frac{s}{\omega_0}+\frac{s^2}{\omega_0^2}=0$, where $\omega_0$ is called the **pole frequency** and $Q$ is called the **pole $Q$ factor** (if $Q>0.5$, poles are complex numbers). ![截圖 2025-01-17 下午6.08.50](https://hackmd.io/_uploads/HyNH2oPv1g.png) ::: **Expressing $Q$ using above parameters**: $Q=\frac{\sqrt{(1+A_0\beta)\omega_{P1}\omega_{P2}}}{\omega_{P1}+\omega_{P2}}$ ![截圖 2025-01-17 下午6.12.46](https://hackmd.io/_uploads/BJy4Tjwvyx.png) ### 10.8.5 Amplifiers with Three or More Poles **Root-locus diagram for an amplifier with 3 poles** ![截圖 2025-01-17 下午6.14.14](https://hackmd.io/_uploads/SyIt6ivDJg.png) $\Rightarrow$ as $\beta\nearrow$, 2 poles reach the right half plane $\Rightarrow$ **become unstable**. ## 10.9 Stability Study Using Bode Plots ### 10.9.1 Gain and Phase Margins ![截圖 2025-01-17 下午6.19.03](https://hackmd.io/_uploads/By9s0jwvJe.png) $\omega_{180}>\omega_1\Rightarrow$ **stable**. (Or, if $|\phi(\omega_1)|>180^{\circ}\Rightarrow$ **unstable**) ### 10.9.2 Effect of Phase Margin on Closed-Loop Response $A(j\omega_1)\beta=1\times e^{-j\theta}$ where $\theta=180^{\circ}-\text{phase margin}$. $\Rightarrow A_f(j\omega_1)=\frac{A(j\omega_1)}{1+A(j\omega_1)\beta}=\frac{(1/\beta)e^{-j\theta}}{1+e^{-j\theta}}$ $\Rightarrow |A_f(j\omega_1)|=\frac{1/\beta}{|1+e^{-j\theta}|}$ Assume that $A_f(0)\simeq\frac{1}{\beta}\Rightarrow\frac{|A_f(j\omega_1)|}{A_f(0)}\simeq\frac{1}{|1+e^{-j\theta}|}$ For example, if phase margin is $45^{\circ}$ ($\theta=135^{\circ}$), then $\frac{|A_f(j\omega_1)|}{A_f(0)}=1.3$. ### 10.9.3 An Alternative Approach for Investigating Stability $20\log|A(j\omega)|-20\log\frac{1}{\beta}=20\log|A\beta|$ ![截圖 2025-01-17 晚上11.12.16](https://hackmd.io/_uploads/B1_DXluDyx.png) $A=\frac{10^5}{(1+jf/10^5)(1+jf/10^6)(1+jf/10^7)}$ $\phi=-[\tan^{-1}(f/10^5)+\tan^{-1}(f/10^6)+\tan^{-1}(f/10^7)]$ When $\phi=-180^{\circ}$, $|A|=60\text{dB}\Rightarrow \beta_{cr}=10^{-3}$ (a)$\beta=5.623\times10^{-5}$, **stable** $\Rightarrow f_1=5.6\times10^5\text{Hz}$ (b)**unstable** :::info ++Observation++. Since the $180^{\circ}$-phase point always occurs on the $-40\text{dB}/\text{decade}$ segment of the Bode plot for $|A|$, the closed-loop amplifier will be stable if the $20\log( 1/\beta)$ line intersects the $20\log|A|$ curve at a point on the $-20\text{dB}/\text{decade}$ segment. Following this rule **ensures that a phase margin of at least $45^{\circ}$** is obtained. The general rule states that at the intersection of $20\log[1/|\beta(j\omega)|]$ and $20 \log|A(j\omega)|$ the difference of slopes (called the **rate of closure**) should not exceed $20\text{dB}/\text{decade}$. ::: ## 10.10 Frequency Compensation ### 10.10.1 Theory $\Rightarrow$ introduce a new pole $f_D$ with low frequency $\Rightarrow A'(s)$ intersects with $20\log(1/\beta)$ with a slope difference of $20\text{dB}/\text{decade}$. ![截圖 2025-01-17 晚上11.32.14](https://hackmd.io/_uploads/ryLE_euP1x.png) :::info ++Note++. Disadvantage: open-loop gain has been drastically reduced. ::: ### 10.10.2 Implementation ![截圖 2025-01-17 晚上11.46.00](https://hackmd.io/_uploads/ByQ8oxOPye.png) $f_{P1}=\frac{1}{2\pi C_xR_x}$ Adding compensating capacitor $C_C$, the pole becomes $f_D'=\frac{1}{2\pi(C_x+C_C)R_x}$ :::info ++Note++. Disadvantage: the required $C_C$ is usually quite large. ::: ### 10.10.3 Miller Compensation and Pole Splitting :::success ++Recall++. Miller effect: ![截圖 2025-01-07 下午6.44.21](https://hackmd.io/_uploads/HkS5pl_vJg.png) ::: ![截圖 2025-01-17 晚上11.54.01](https://hackmd.io/_uploads/H1nm6lOPkx.png) ($C_1$ includes the miller component of $C_\mu$, $C_2$ includes $C_L$) If there is no compensating capacitor $C_f$, $\Rightarrow f_{P1}=\frac{1}{2\pi C_1R_1}$, $f_{P2}=\frac{1}{2\pi C_2R_2}$ When $C_f$ is added: $\Rightarrow\frac{V_o}{I_i}=\frac{(sC_f-g_m)R_1R_2}{1+s[C_1R_1+C_2R_2+C_f(g_mR_1R_2+R_1+R_2)]+s^2[C_1C_2+C_f(C_1+C_2)]R_1R_2}$ Rewrite the denominator $D(s)$, we have ($\omega_{P1}' \ll \omega_{P2}'$) $D(s)=\left(1+\frac{s}{\omega_{P1}'}\right)\left(1+\frac{s}{\omega_{P2}'}\right)=1+s\left(\frac{1}{\omega_{P1}'}+\frac{1}{\omega_{P2}'}\right)+\frac{s^2}{\omega_{P1}'\omega_{P2}'}\simeq1+\frac{s}{\omega_{P1}'}+\frac{s^2}{\omega_{P1}'\omega_{P2}'}$ $\Rightarrow \omega_{P1}'=\frac{1}{C_1R_1+C_2R_2+C_f(g_mR_1R_2+R_1+R_2)}\simeq\frac{1}{g_mR_2C_fR_1}$ $\Rightarrow\omega_{P2}'\simeq\frac{g_mC_f}{C_1C_2+C_f(C_1+C_2)}$ :::info ++Observation++. As $C_f$ increases, $\omega_{P1}'$ is reduced and $\omega_{P2}'$ is increased (**pole splitting**). Also, because of the Miller effect, $C_f$ is increased by $g_mR_2$ and hence can be smaller than that of $C_C$ in 10.10.2. ::: ## Summary - The key parameter in a feedback amplifier is the **loop gain** $A\beta$ (and the amount of feedback $(1+A\beta)$). - The closed-loop gain can be expressed as $A_f=\frac{A}{1+A\beta}$. - The ideal value of $A_f$ is $A_f|_{\text{ideal}}=\frac{1}{\beta}$, happens when the open loop gain $A$ is large. - $A\beta$ can be determined by breaking the feedback loop (set $x_s=0\Rightarrow A\beta=-\frac{x_r}{x_t}$). - $\beta$ can be determined finding $\beta=\frac{x_s}{x_o}$ under the condition $x_i=0$ (i.e., $A=\infty$). - The properties of four types of feedback topologies are described in section [10.5.1](https://hackmd.io/fWlf9XhPQxykpzsLwgKfkA#1051-Basic-Principles). - A series connection at the input or output of a feedback amplifier increases the resistance by $(1+A\beta)$. - A parallel (shunt) connection reduces the resistance by $(1+A\beta)$. - Method of analysing a feedback amplifier: - **Begin by finding $A_f|_{\text{ideal}}$**. - Sketch the two-port feedback circuit and determine its loading effects $R_{11}$ and $R_{22}$. - Sketch the A circuit and analyze it to determine $A$, $R_i$, and $R_o$. - Calculate $A\beta$ and the amount of feedback $(1+A\beta)$. - Use formulas to determine $A_f$, $R_{if}$ and $R_{of}$. - Stability (frequency response of the feedback amplifier) - The poles are determined by the characteristic equation $1+A(s)\beta(s)=0$. - For the amplifier to be stable, **all poles should be in the left half of the s plane**. - Also, if at the frequency for which the phase shift of $A\beta$ is $180^{\circ}$ ($\omega_{180}$), we have $|A\beta|<1$, then the amplifier is stable. (The amount by which it is less than $1$, in $\text{dB}$, is the **gain margin**.) - Alternatively, if at the frequency for which $|A\beta|=1$ (named $\omega_1$), the phase angle is less than $180^{\circ}$, then the amplifier is stable. (The difference is called the **phase margin**.) - We can also check the stability by analyzing the Bode plot of $|A|$ and the curve of $20\log(1/|\beta|)$. Stability is guaranteed if two lines intersect with a difference in slope no greater than $20\text{dB}/\text{decade}$. - Frequency compensation is the process where we modify the frequency of the pole for the given $\beta$ in order to make the amplifier stable. ## Practice - 10.1, 10.2, 10.3 - 10.10, 10.11, 10.12, 10.13, 10.14, 10.15, 10.16 - 10.24, 10.25, 10.26 - 10.32, 10.33 - 10.43, 10.50, 10.61, 10.71 - 10.81 - 10.83 - 10.89, 10.90 - 10.95, 10.96