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Robust Stability and Worst-Case Gain of Uncertain System

This example shows how to calculate the robust stability and examine the worst-case gain of the closed-loop system described in System with Uncertain Parameters. The following commands construct that system.

m1 = ureal('m1',1,'percent',20);
m2 = ureal('m2',1,'percent',20);
k  = ureal('k',1,'percent',20);

s = zpk('s');
G1 = ss(1/s^2)/m1;
G2 = ss(1/s^2)/m2;

F = [0;G1]*[1 -1]+[1;-1]*[0,G2];
P = lft(F,k);

C = 100*ss((s+1)/(.001*s+1))^3;

T = feedback(P*C,1); % Closed-loop uncertain system

This uncertain state-space model T has three uncertain parameters, k, m1, and m2, each equal to 1±20% uncertain variation. Use robstab to analyze whether the closed-loop system T is robustly stable for all combinations of possible values of these three parameters.

[stabmarg,wcus] = robstab(T);
stabmarg = 

  struct with fields:

           LowerBound: 2.8828
           UpperBound: 2.8864
    CriticalFrequency: 575.0338

The data in the structure stabmarg includes bounds on the stability margin, which indicate that the control system can tolerate almost 3 times the specified uncertainty before going unstable. It is stable for all parameter variations in the specified ±20% range. The critical frequency is the frequency at which the system is closest to instability.

The structure wcus contains the smallest destabilization perturbation values for each uncertain element.

wcus = 

  struct with fields:

     k: 1.5773
    m1: 0.4227
    m2: 0.4227

You can use these values with usubs to verify that they do indeed result in an unstable system.

Tunst = usubs(T,wcus);
ans =



Use wcgain to calculate the worst-case peak gain, the highest peak gain occurring within the specified uncertainty ranges.

[wcg,wcug] = wcgain(T);
wcg = 

  struct with fields:

           LowerBound: 1.0475
           UpperBound: 1.0796
    CriticalFrequency: 6.7143

wcug contains the values of the uncertain elements that cause the worst-case gain. Compute a closed-loop model with these values, and plot its frequency response along with some random samples of the uncertain system.

Twc = usubs(T,wcug);
Trand = usample(T,5);
legend('Twc - worst-case','Trand - random samples','Location','SouthWest');

Alternatively use wcsigma to visualize the highest possible gain at each frequency, the system with the highest peak gain, and random samples of the uncertain system.


See Also

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