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| drmodel, drss | Examples See Also |
Generate stable random discrete test models
Syntax
sys = drss(n) sys = drss(n,p) sys = drss(n,p,m)sys = drss(n,p,m,s1,...sn)
[num,den] = drmodel(n) [A,B,C,D] = drmodel(n) [A,B,C,D] = drmodel(n,p,m)
Description
sys = drss(n)
produces a random n-th order stable model with one input and one output, and returns the model in the state-space object sys.
drss(n,p)
produces a random n-th order stable model with one input and p outputs.
drss(n,m,p)
generates a random n-th order stable model with m inputs and p outputs.
drss(n,p,m,s1,...sn)
generates a s1-by-sn array of random n-th order stable model with m inputs and p outputs.
In all cases, the discrete-time state-space model or array returned by drss has an unspecified sampling time. To generate transfer function or zero-pole-gain systems, convert sys using tf or zpk.
drmodel(n)
produces a random n-th order stable model and returns either the transfer function numerator num and denominator den or the state-space matrices A, B, C, and D, based on the number of output arguments. The resulting model always has one input and one output.
[A,B,C,D] = drmodel(n,m,p)
produces a random n-th order stable state-space model with m inputs and p outputs.
Example
Generate a random discrete LTI system with three states, two inputs, and two outputs.sys = drss(3,2,2)
a =
x1 x2 x3
x1 0.38630 -0.21458 -0.09914
x2 -0.23390 -0.15220 -0.06572
x3 -0.03412 0.11394 -0.22618
b =
u1 u2
x1 0.98833 0.51551
x2 0 0.33395
x3 0.42350 0.43291
c =
x1 x2 x3
y1 0.22595 0.76037 0
y2 0 0 0
d =
u1 u2
y1 0 0.68085
y2 0.78333 0.46110
Sampling time: unspecified
Discrete-time system.
See Also
rmodel, rss Generate stable random continuous test models
tf Convert LTI systems to transfer functions form
zpk Convert LTI systems to zero-pole-gain form