Specifications
Table Of Contents
- Introduction
- LTI Models
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- Arrays of LTI Models
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- Function Reference
- Functions by Category
- acker
- allmargin
- append
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- ctrb
- ctrbf
- d2c
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- damp
- dare
- dcgain
- delay2z
- dlqr
- dlyap
- drss
- dsort
- dss
- dssdata
- esort
- estim
- evalfr
- feedback
- filt
- frd
- frdata
- freqresp
- gensig
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- gram
- hasdelay
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- ndims
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- nyquist
- obsv
- obsvf
- ord2
- pade
- parallel
- place
- pole
- pzmap
- reg
- reshape
- rlocus
- rss
- series
- set
- sgrid
- sigma
- sisotool
- size
- sminreal
- ss
- ss2ss
- ssbal
- ssdata
- stack
- step
- tf
- tfdata
- totaldelay
- zero
- zgrid
- zpk
- zpkdata
- Index

rss
16-182
16rss
Purpose 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)
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,orzpk to convert the state-space object sys to transfer function,
frequency response, or zero-pole-gain form.
Example Obtain a stable random continuous LTI model with three states, two inputs,
and two outputs by typing
sys = 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