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

canon
11-28
For state-space models sys,
[csys,T] = canon(a,b,c,d,'type')
also returns the state coordinate transformation T relating the original state
vector and the canonical sta te vector .
This syntax returns
T=[] when sys is not a state-space model.
Algorithm Transfer functions or zero-pole-gain models are first converted to state space
using
ss.
The transformation to modal form uses the matrix of eigenvectors o f the
matrix. The modal form is then obtained as
The state transformation returned is the inverse of .
The reduction to companion form uses a state similarity transformation based
on the controllability matrix [1].
Limitations The modal transformation requires that the matrix be diagonalizable. A
sufficientconditionfor diagonalizability is that hasno repeated eigenvalues.
The companion transformation requires that the system be controllable from
the first input. The companion form is often poorly conditioned for most
state-space computations; avoid using it when possible.
See Also ctrb Controllability matrix
ctrbf Controllability canonical form
ss2ss State similarity transformation
References [1] Kailath, T. L inear Systems, Prentice-Hall, 1980.
x
x
c
x
c
Tx
=
P
A
x
c
·
P
1
–
APx
c
P
1
–
Bu+=
yCPx
c
Du+=
T
P
A
A