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uscale

Scale uncertainty of block or system

Since R2020a

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Syntax

blk_scaled = uscale(blk,factor)
M_scaled = uscale(M,factor)

Description

blk_scaled = uscale(blk,factor) scales the amount of uncertainty in an uncertain control design block by factor. Typically, factor is a robustness margin returned by robstab or robgain, or a robust performance returned by musynperf. The uncertain element blk_scaled is of the same type as blk, with the amount of uncertainty scaled in normalized units. For instance, if factor is 0.75, the normalized uncertainty of blk_scaled is 75% of the normalized uncertainty of blk.

example

M_scaled = uscale(M,factor) scales all the uncertain blocks in the model M. Non-uncertain elements are not changed.

example

Examples

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Open Live Script

Consider a feedback loop with the following open-loop gain. 

L = tf(3.5,[1 2 3 0]);

Suppose that the system has gain uncertainty of 1.5 (gain can increase or decrease by a factor of 1.5) and phase uncertainty of ±30°.

DGM = getDGM(1.5,30,'tight');
F = umargin('F',DGM)
Uncertain gain/phase "F" with relative gain change in [0.472,1.5] and phase change of ±30 degrees.

Examine the robust stability of the closed-loop system.

T = feedback(L*F,1);
SM = robstab(T)
SM = struct with fields:
           LowerBound: 0.8303
           UpperBound: 0.8319
    CriticalFrequency: 1.4482

robstab shows that the system can only tolerate 0.83 times the modeled uncertainty before going unstable. Scale the umargin block F by this amount to find the largest gain and phase variation that the system can tolerate. 

factor = SM.LowerBound;
Fsafe = uscale(F,factor)
Uncertain gain/phase "F" with relative gain change in [0.563,1.42] and phase change of ±24.8 degrees.

The scaled uncertainty has smaller ranges of both gain variation and phase variation. Compare these ranges for the original modeled variation and the maximum tolerable variation. 

DGM = F.GainChange;
DGMsafe = Fsafe.GainChange;
diskmarginplot([DGM;DGMsafe])
legend('original','safe')

MATLAB figure

Open Live Script

Consider the uncertain control system of the example "Robust Performance of Closed-Loop System" on the robgain reference page. That example examines the sensitivity of the closed-loop response at the plant output to disturbances at the plant input. 

k = ureal('k',10,'Percent',40);
delta = ultidyn('delta',[1 1]); 
G = tf(18,[1 1.8 k]) * (1 + 0.5*delta);
C = pid(2.3,3,0.38,0.001);
S = feedback(1,G*C)
Uncertain continuous-time state-space model with 1 outputs, 1 inputs, 4 states.
The model uncertainty consists of the following blocks:
  delta: Uncertain 1x1 LTI, peak gain = 1, 1 occurrences
  k: Uncertain real, nominal = 10, variability = [-40,40]%, 1 occurrences

Type "S.NominalValue" to see the nominal value and "S.Uncertainty" to interact with the uncertain elements.

Suppose that you do not want the peak gain of this sensitivity function to exceed 1.5. Use robgain to find out how much of the modeled uncertainty the system can tolerate while the peak gain remains below 1.5.

perfmarg = robgain(S,1.5)
perfmarg = struct with fields:
           LowerBound: 0.7821
           UpperBound: 0.7837
    CriticalFrequency: 7.8566

With that performance requirement, the system can only tolerate about 78% of the modeled uncertainty. Scale all the uncertain elements in S to create a model of the closed-loop system with the maximum level of uncertainty that meets the performance requirement. 

factor = perfmarg.LowerBound;
S_scaled = uscale(S,factor)
Uncertain continuous-time state-space model with 1 outputs, 1 inputs, 4 states.
The model uncertainty consists of the following blocks:
  delta: Uncertain 1x1 LTI, peak gain = 0.782, 1 occurrences
  k: Uncertain real, nominal = 10, variability = [-31.3,31.3]%, 1 occurrences

Type "S_scaled.NominalValue" to see the nominal value and "S_scaled.Uncertainty" to interact with the uncertain elements.

The display shows how the uncertain elements in S_scaled have changed: the peak gain of the ultidyn element delta is reduced from 1 to 0.78, and the range of variation of the uncertain real parameter k is reduced from ±40% to ±31.3%.

Input Arguments

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Uncertain control design block to scale, specified as a ureal, umargin, ultidyn, or other uncertain block.

Scaling factor, specified as a scalar. This argument is the amount by which uscale scales the normalized uncertainty of blk or M. For instance, if factor = 0.8, then the function reduces the uncertainty to 80% of its original value, in normalized units. Similarly, if factor = 2, then the function doubles the uncertainty.

Typically, factor is a robustness margin returned by robstab or robgain, or a robust performance returned by musynperf. Thus, you can use uscale to find the largest range of modeled uncertainty in a system for which the system has good robust stability or performance.

Uncertain model, specified as a uss, umat, ufrd, or genss with uncertain control design blocks. The uscale command scales uncertain control design blocks in M. Other blocks of M are unchanged.

Output Arguments

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Scaled uncertain block, returned as a block of the same type as blk, such as a ureal, umargin, ultidyn, or other uncertain block. The uncertainty of blk_scaled is the same as the uncertainty in M, scaled by factor.

Scaled uncertain model, returned as a model of the same type as M, such as a uss, umat, ufrd, or genss with uncertain control design blocks. The uncertain control design blocks in M_scaled are the same as the blocks in M, with the size of uncertainty scaled by factor in normalized units.

Version History

Introduced in R2020a

See Also

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