User`s guide
Table Of Contents
- Preface
- Quick Start
- LTI Models
- Introduction
- Creating LTI Models
- LTI Properties
- Model Conversion
- Time Delays
- Simulink Block for LTI Systems
- References
- Operations on LTI Models
- Arrays of LTI Models
- Model Analysis Tools
- The LTI Viewer
- Introduction
- Getting Started Using the LTI Viewer: An Example
- The LTI Viewer Menus
- The Right-Click Menus
- The LTI Viewer Tools Menu
- Simulink LTI Viewer
- Control Design Tools
- The Root Locus Design GUI
- Introduction
- A Servomechanism Example
- Controller Design Using the Root Locus Design GUI
- Additional Root Locus Design GUI Features
- References
- Design Case Studies
- Reliable Computations
- Reference
- Category Tables
- acker
- append
- augstate
- balreal
- bode
- c2d
- canon
- care
- chgunits
- connect
- covar
- ctrb
- ctrbf
- d2c
- d2d
- damp
- dare
- dcgain
- delay2z
- dlqr
- dlyap
- drmodel, drss
- dsort
- dss
- dssdata
- esort
- estim
- evalfr
- feedback
- filt
- frd
- frdata
- freqresp
- gensig
- get
- gram
- hasdelay
- impulse
- initial
- inv
- isct, isdt
- isempty
- isproper
- issiso
- kalman
- kalmd
- lft
- lqgreg
- lqr
- lqrd
- lqry
- lsim
- ltiview
- lyap
- margin
- minreal
- modred
- ndims
- ngrid
- nichols
- norm
- nyquist
- obsv
- obsvf
- ord2
- pade
- parallel
- place
- pole
- pzmap
- reg
- reshape
- rlocfind
- rlocus
- rltool
- rmodel, rss
- series
- set
- sgrid
- sigma
- size
- sminreal
- ss
- ss2ss
- ssbal
- ssdata
- stack
- step
- tf
- tfdata
- totaldelay
- zero
- zgrid
- zpk
- zpkdata
- Index

covar
11-40
11covar
Purpose Output and state covariance of a system driven by white noise
Syntax [P,Q] = covar(sys,W)
Description covar calculates the stationary covariance of the output of an LTI model sys
driven by Gaussian white noise inputs . This function handles both
continuous- and discrete-time cases.
P = covar(sys,W) returns t he steady-state output response covariance
given the noise intensity
[P,Q] = covar(sys,W) also returns the steady-state state covariance
when
sys is a state-space model (otherwise Q is set to []).
When applied to an
N-dimensional LTI array sys, covar returns
multi-dimensional a rrays P, Q such that
P(:,:,i1,...iN) and Q(:,:,i1,...iN) are t he covaria nce matrices for the
model s
ys(:,:,i1,...iN).
Example Compute the output response covariance of the discrete SISO system
due to Gaussian white noise of intensity
W = 5.Type
sys = tf([2 1],[1 0.2 0.5],0.1);
p = covar(sys,5)
y
w
PEyy
T
()=
Ewt()wτ()
T
()Wδtτ–()= (continuous time)
Ewk[]wl[]
T
()Wδ
kl
= (discrete time)
QExx
T
()=
Hz()
2z 1
+
z
2
0.2 z 0.5++
--------------------------------------
,= T
s
0.1=