In integrated circuit design, an advanced field-effect transistor (FET) regulates output current based on gate-to-source voltage (V g V_g V g ) and drain-to-source voltage (V d V_d V d ). In the saturation regime, the electrical drain current I I I (in milliamperes, mA \text{mA} mA ) is modeled by the non-linear constitutive equation:
I ( V g , V d ) = V g 3 + V d 2 I(V_g, V_d) = \sqrt{V_g^3 + V_d^2} I ( V g , V d ) = V g 3 + V d 2
The transistor's nominal operating bias point (Q-point) is established at V g = 2.0 V V_g = 2.0\text{ V} V g = 2.0 V and V d = 4.0 V V_d = 4.0\text{ V} V d = 4.0 V , providing a baseline current of:
I ( 2 , 4 ) = 2 3 + 4 2 = 8 + 16 = 24 ≈ 4.8990 mA I(2, 4) = \sqrt{2^3 + 4^2} = \sqrt{8 + 16} = \sqrt{24} \approx 4.8990\text{ mA} I ( 2 , 4 ) = 2 3 + 4 2 = 8 + 16 = 24 ≈ 4.8990 mA
During high-frequency switching, power rail switching noise causes the terminal voltages to shift slightly to an off-nominal state of V g = 2.02 V V_g = 2.02\text{ V} V g = 2.02 V and V d = 3.95 V V_d = 3.95\text{ V} V d = 3.95 V .
State the multivariable total differential formula d I dI d I for the transistor current in terms of voltage differentials d V g dV_g d V g and d V d dV_d d V d .
Compute the analytical partial derivatives ∂ I ∂ V g \frac{\partial I}{\partial V_g} ∂ V g ∂ I and ∂ I ∂ V d \frac{\partial I}{\partial V_d} ∂ V d ∂ I , and evaluate them at the nominal bias point ( 2 , 4 ) (2, 4) ( 2 , 4 ) .
Use the linear approximation L ( V g , V d ) L(V_g, V_d) L ( V g , V d ) centered at ( 2 , 4 ) (2, 4) ( 2 , 4 ) to estimate the perturbed current I ( 2.02 , 3.95 ) mA I(2.02, 3.95)\text{ mA} I ( 2.02 , 3.95 ) mA .
If manufacturer power rail tolerances guarantee ∣ d V g ∣ ≤ 0.05 V |dV_g| \le 0.05\text{ V} ∣ d V g ∣ ≤ 0.05 V and ∣ d V d ∣ ≤ 0.10 V |dV_d| \le 0.10\text{ V} ∣ d V d ∣ ≤ 0.10 V , compute the maximum worst-case current fluctuation ∣ d I ∣ max |dI|_{\max} ∣ d I ∣ m a x .
Step-by-Step Solution:
State the Total Differential Formula:
As defined in Differentials and Error Propagation , the total differential d I dI d I is:
d I = ∂ I ∂ V g d V g + ∂ I ∂ V d d V d dI = \frac{\partial I}{\partial V_g} dV_g + \frac{\partial I}{\partial V_d} dV_d d I = ∂ V g ∂ I d V g + ∂ V d ∂ I d V d
Compute Analytical Partial Derivatives:
Let u ( V g , V d ) = V g 3 + V d 2 u(V_g, V_d) = V_g^3 + V_d^2 u ( V g , V d ) = V g 3 + V d 2 . Applying the Generalized Power Rule:
∂ I ∂ V g = 1 2 ( V g 3 + V d 2 ) − 1 / 2 ( 3 V g 2 ) = 3 V g 2 2 V g 3 + V d 2 \frac{\partial I}{\partial V_g} = \frac{1}{2}(V_g^3 + V_d^2)^{-1/2}(3V_g^2) = \frac{3V_g^2}{2\sqrt{V_g^3 + V_d^2}} ∂ V g ∂ I = 2 1 ( V g 3 + V d 2 ) − 1/2 ( 3 V g 2 ) = 2 V g 3 + V d 2 3 V g 2
∂ I ∂ V d = 1 2 ( V g 3 + V d 2 ) − 1 / 2 ( 2 V d ) = V d V g 3 + V d 2 \frac{\partial I}{\partial V_d} = \frac{1}{2}(V_g^3 + V_d^2)^{-1/2}(2V_d) = \frac{V_d}{\sqrt{V_g^3 + V_d^2}} ∂ V d ∂ I = 2 1 ( V g 3 + V d 2 ) − 1/2 ( 2 V d ) = V g 3 + V d 2 V d
Evaluate at ( V g , V d ) = ( 2 , 4 ) (V_g, V_d) = (2, 4) ( V g , V d ) = ( 2 , 4 ) , where V g 3 + V d 2 = 24 = 2 6 \sqrt{V_g^3 + V_d^2} = \sqrt{24} = 2\sqrt{6} V g 3 + V d 2 = 24 = 2 6 :
∂ I ∂ V g ∣ ( 2 , 4 ) = 3 ( 2 2 ) 2 24 = 12 2 24 = 6 24 = 3 6 ≈ 1.2247 mA/V \left.\frac{\partial I}{\partial V_g}\right|_{(2, 4)} = \frac{3(2^2)}{2\sqrt{24}} = \frac{12}{2\sqrt{24}} = \frac{6}{\sqrt{24}} = \frac{3}{\sqrt{6}} \approx 1.2247\text{ mA/V} ∂ V g ∂ I ( 2 , 4 ) = 2 24 3 ( 2 2 ) = 2 24 12 = 24 6 = 6 3 ≈ 1.2247 mA/V
∂ I ∂ V d ∣ ( 2 , 4 ) = 4 24 = 2 6 ≈ 0.8165 mA/V \left.\frac{\partial I}{\partial V_d}\right|_{(2, 4)} = \frac{4}{\sqrt{24}} = \frac{2}{\sqrt{6}} \approx 0.8165\text{ mA/V} ∂ V d ∂ I ( 2 , 4 ) = 24 4 = 6 2 ≈ 0.8165 mA/V
Construct Linear Approximation and Estimate Current:
Formulate the linearization function centered at ( 2 , 4 ) (2, 4) ( 2 , 4 ) :
L ( V g , V d ) = I ( 2 , 4 ) + ∂ I ∂ V g ∣ ( 2 , 4 ) ( V g − 2 ) + ∂ I ∂ V d ∣ ( 2 , 4 ) ( V d − 4 ) L(V_g, V_d) = I(2, 4) + \left.\frac{\partial I}{\partial V_g}\right|_{(2, 4)}(V_g - 2) + \left.\frac{\partial I}{\partial V_d}\right|_{(2, 4)}(V_d - 4) L ( V g , V d ) = I ( 2 , 4 ) + ∂ V g ∂ I ( 2 , 4 ) ( V g − 2 ) + ∂ V d ∂ I ( 2 , 4 ) ( V d − 4 )
L ( V g , V d ) = 24 + 6 24 ( V g − 2 ) + 4 24 ( V d − 4 ) L(V_g, V_d) = \sqrt{24} + \frac{6}{\sqrt{24}}(V_g - 2) + \frac{4}{\sqrt{24}}(V_d - 4) L ( V g , V d ) = 24 + 24 6 ( V g − 2 ) + 24 4 ( V d − 4 )
Calculate offsets for target point ( 2.02 , 3.95 ) (2.02, 3.95) ( 2.02 , 3.95 ) :
Δ V g = 2.02 − 2.0 = + 0.02 V \Delta V_g = 2.02 - 2.0 = +0.02\text{ V} Δ V g = 2.02 − 2.0 = + 0.02 V
Δ V d = 3.95 − 4.0 = − 0.05 V \Delta V_d = 3.95 - 4.0 = -0.05\text{ V} Δ V d = 3.95 − 4.0 = − 0.05 V
Substitute offsets:
L ( 2.02 , 3.95 ) = 24 + 6 ( 0.02 ) + 4 ( − 0.05 ) 24 = 24 + 0.12 − 0.20 24 = 24 − 0.08 24 L(2.02, 3.95) = \sqrt{24} + \frac{6(0.02) + 4(-0.05)}{\sqrt{24}} = \sqrt{24} + \frac{0.12 - 0.20}{\sqrt{24}} = \sqrt{24} - \frac{0.08}{\sqrt{24}} L ( 2.02 , 3.95 ) = 24 + 24 6 ( 0.02 ) + 4 ( − 0.05 ) = 24 + 24 0.12 − 0.20 = 24 − 24 0.08
L ( 2.02 , 3.95 ) ≈ 4.89898 − 0.08 4.89898 ≈ 4.89898 − 0.01633 ≈ 4.8827 mA L(2.02, 3.95) \approx 4.89898 - \frac{0.08}{4.89898} \approx 4.89898 - 0.01633 \approx 4.8827\text{ mA} L ( 2.02 , 3.95 ) ≈ 4.89898 − 4.89898 0.08 ≈ 4.89898 − 0.01633 ≈ 4.8827 mA
Compute Worst-Case Current Fluctuation:
Applying the Triangle Inequality for maximum error bound:
∣ d I ∣ max ≤ ∣ ∂ I ∂ V g ∣ ∣ d V g ∣ + ∣ ∂ I ∂ V d ∣ ∣ d V d ∣ |dI|_{\max} \le \left|\frac{\partial I}{\partial V_g}\right| |dV_g| + \left|\frac{\partial I}{\partial V_d}\right| |dV_d| ∣ d I ∣ m a x ≤ ∂ V g ∂ I ∣ d V g ∣ + ∂ V d ∂ I ∣ d V d ∣
∣ d I ∣ max ≤ ( 1.2247 ) ( 0.05 ) + ( 0.8165 ) ( 0.10 ) = 0.06124 + 0.08165 = 0.1429 mA |dI|_{\max} \le (1.2247)(0.05) + (0.8165)(0.10) = 0.06124 + 0.08165 = 0.1429\text{ mA} ∣ d I ∣ m a x ≤ ( 1.2247 ) ( 0.05 ) + ( 0.8165 ) ( 0.10 ) = 0.06124 + 0.08165 = 0.1429 mA
The maximum current deviation due to power rail noise is bounded by approximately ± 0.143 mA \pm 0.143\text{ mA} ± 0.143 mA (or 0.1429 4.8990 × 100 % ≈ 2.92 % \frac{0.1429}{4.8990} \times 100\% \approx 2.92\% 4.8990 0.1429 × 100% ≈ 2.92% ).