Closed-loop Gain and Sensitivity

English translation

Control Engineering I · Week 9

This week's objective · Compare how much amplifier gain changes affect the final output.

Run: After signing in to MathWorks, open .mlx in your workspace. Click inside the code → Live Editor → Run Section to run one section at a time. Run runs everything. After changing a value, rerun the relevant section. Edit the text in ⟦enter here⟧ response fields; do not execute them. You can use Ctrl+Enter on Windows/Linux and ⌘+Enter on Mac.

1. Sensitivity of an open-loop amplifier

The overall open-loop gain is T=KaK_a. If KaK_a increases by 10%, T also increases by 10%. Sensitivity starts from this ratio of relative changes being 1.

Sensitivity of an open-loop amplifier

For example, if a 1% change in amplifier gain produces approximately a 1% change in overall gain, the sensitivity is 1. If the overall gain changes by only about 0.1%, the sensitivity is 0.1. To compare changes in quantities of different magnitudes, use the change relative to each original value rather than the change alone.

The relative change in KaK_a is ΔKa/Ka\Delta K_a/K_a, and that in TT is ΔT/T\Delta T/T. For very small changes, the normalized sensitivity relating these two ratios is

SKaT=KaTdTdKaS_{K_a}^T=\frac{K_a}{T}\frac{dT}{dK_a}

. The derivative calculated below shows how much the overall gain responds to a small change in amplifier gain.

2. Express the effect of feedback mathematically

In this example, βy\beta y of the output is measured and compared with the reference, so y=Ka(r−βy)y=K_a(r-\beta y). Collecting the yy terms gives (1+Kaβ)y=Kar(1+K_a\beta)y=K_a r, and the overall gain is as follows.

T=yr=Ka1+Kaβ.T=\frac yr=\frac{K_a}{1+K_a\beta}.

As KaK_a increases, both numerator and denominator increase. The overall gain therefore changes less sensitively than the amplifier gain. Calculate the degree using the sensitivity definition above.

Express the effect of feedback mathematically

Holding β\beta fixed and differentiating the TT just obtained, the quotient rule gives

dTdKa=(1+βKa)−βKa(1+βKa)2=1(1+βKa)2.\frac{dT}{dK_a}=\frac{(1+\beta K_a)-\beta K_a}{(1+\beta K_a)^2}=\frac1{(1+\beta K_a)^2}.

Multiplying this by the previously obtained Ka/T=1+βKaK_a/T=1+\beta K_a gives

SKaT=KaTdTdKa=11+βKa.S_{K_a}^T=\frac{K_a}{T}\frac{dT}{dK_a}=\frac1{1+\beta K_a}.

The full overall-gain expression is used to calculate normalized sensitivity. As βKa\beta K_a increases, this ratio decreases, so the overall gain changes less for the same amplifier-gain change.

The inverting amplifier from the lecture is represented by T=−Ka/(1+βKa)T=-K_a/(1+\beta K_a). Here, both TT and its derivative have negative signs, so normalized sensitivity is the same as above.

This amplifier model omits dynamics and noise. In a real controller, when increasing the gain, also check oscillation and measurement-noise effects.

3. Compare actual changes with approximations

The assignment conditions are KaK_a=5000 and β=0.05. Compare the change predicted by Sensitivity×0.1 with the relative change calculated directly by setting KaK_a to 5500.

Compare actual changes with approximations

Let the value before the change be K0K_0 and the corresponding overall gain be T0=T(K0)T_0=T(K_0). As with the linear approximation in Week 3, estimating the change from the slope at the reference point gives

ΔT≈T′(K0)ΔKa.\Delta T\approx T'(K_0)\Delta K_a.

Divide both sides by T0T_0, then multiply and divide by K0K_0 to obtain the sensitivity found earlier.

ΔTT0≈[K0T0T′(K0)]ΔKaK0=S0ΔKaK0.\frac{\Delta T}{T_0}\approx\left[\frac{K_0}{T_0}T'(K_0)\right]\frac{\Delta K_a}{K_0}=S_0\frac{\Delta K_a}{K_0}.

For a +10% change, therefore, use S0×0.1S_0\times0.1. This estimate uses the slope at the reference point. For the exact value, insert the new gain into the original T(Ka)T(K_a) expression to obtain T1T_1, then calculate (T1−T0)/T0(T_1-T_0)/T_0. Both methods divide by the unchanged T0T_0. Multiply by 100 only at the end when expressing the result as a percentage.

In this exercise, compare relative changes of 1%, 10%, and 20%. As the change grows, check how far an estimate using only the slope at the baseline point deviates from the actual change.

4. Interpret the results in words

Compare KaK_a, open-loop gain, and closed-loop gain in a table or plot, then explain which changed less. Distinguish a small closed-loop gain from lower sensitivity to change.

Interpret the results in words

Changing β also changes the target gain. State whether the experiment compares the same target or different feedback strengths.

Check your understanding

  1. What values should go into the code, and what does each row and column of the resulting array represent? If calculating physical quantities, have you also checked the units?
  2. Can you identify which parts to rerun when you change one condition?
  3. Do the results match your expectations? If they differ, can you explain why using the output values or plots?

Official MATLAB documentation · Control System Toolbox

Practice materials