| Control System Toolbox | Search Help Desk |
| rmodel, rss | Examples See Also |
Generate stable random continuous test models
Syntax
sys = rss(n) sys = rss(n,p) sys = rss(n,p,m)sys = rss(n,p,m,s1,...,sn)
[num,den] = rmodel(n) [A,B,C,D] = rmodel(n) [A,B,C,D] = rmodel(n,p,m)
Description
rss(n)
produces a stable random n-th order model with one input and one output and returns the model in the state-space object sys.
rss(n,p)
produces a random nth order stable model with one input and p outputs, and rss(n,m,p) produces a random n-th order stable model with m inputs and p outputs. The output sys is always a state-space model.
rss(n,p,m,s1,...,sn)produces an s1-by-...-by-sn array of random n-th order stable state-space models with m inputs and p outputs.
Use tf, frd, or zpk to convert the state-space object sys to transfer function, frequency response, or zero-pole-gain form.
rmodel(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, depending on the number of output arguments. The resulting model always has one input and one output.
[A,B,C,D] = rmodel(n,m,p)
produces a stable random nth order state-space model with m inputs and p outputs.
Example
Obtain a stable random continuous LTI model with three states, two inputs, and two outputs by typingsys = rss(3,2,2)
a =
x1 x2 x3
x1 -0.54175 0.09729 0.08304
x2 0.09729 -0.89491 0.58707
x3 0.08304 0.58707 -1.95271
b =
u1 u2
x1 -0.88844 -2.41459
x2 0 -0.69435
x3 -0.07162 -1.39139
c =
x1 x2 x3
y1 0.32965 0.14718 0
y2 0.59854 -0.10144 0.02805
d =
u1 u2
y1 -0.87631 -0.32758
y2 0 0
Continuous-time system.
See Also
drmodel, drss Generate stable random discrete test models
frd Convert LTI systems to frequency response form
tf Convert LTI systems to transfer function form
zpk Convert LTI systems to zero-pole-gain form