controllability of large scale networks - math.unipd.itmotta/controllability-zampieri.pdf · sandro...

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Sandro Zampieri

Universita’ di Padova

In collaboration with

Fabio Paqualetti - University of California at Riverside

Francesco Bullo - University of California at Santa Barbara

Controllability of large scale networks

1

Large scale networks

2

US electric grid

References: controllability of complex networks

References: classical results

Problem formulation

5

( + ) = ( ) + ( )

!

= [ · · · ]

=

!

""""""""""#

$

%%%%%%%%%%&

A controllability metric

6

Controlled node

A controllability metric

7

8

A controllability metric

! ( )

:=!!

=

=! ( )

! ( )

! ( )

9

Conditions ensuring low controllability

( )

( )

< <

( ) := |{! ! !( ) : |!| " }|

! ( ) "( # )

( )

10

US electric grid

Conditions ensuring low controllability

11

Example: consensus with circle graph

=

!

""""""""""""#

/ / . . . . . . // / / · · · · · ·

/ / · · ·

· · · / // · · · · · · / /

$

%%%%%%%%%%%%&

12

Example: consensus with circle graph

/

/

! /

13

Example: consensus with circle graph

/

/

! /

!

14

Example: consensus with circle graph

/

/

! /

!

15

High controllability and controllers positioning

V = { , . . . , } V , . . . ,V

=

!

"#· · ·

· · ·

$

%& , =

!

"#· · ·

· · ·

$

%& ,

( + ) = ( ) +'

!N( ) + ( ),

! { , . . . , } N := { : "= }

16

High controllability and controllers positioning

! V"= ! V! , ! ! { , . . . , } "= !

B # V

B =!

=

B

17

High controllability and controllers positioning

18

High controllability and controllers positioning

( ) := ( )!!

!N( )

( + ) = ( ) + ( )

,

19

High controllability and controllers positioning

! := (!! ( , ), . . . ,!! ( , )),

" :=

!

""""#

" · · · "" · · · "

" "

$

%%%%&,

" = ! ( " )! ! !

! ( ) #!"! / !

,

20

High controllability and controllers positioning

! :=

!

"""#

! ! · · · ! !! ! · · · ! !

! ! ! ! · · ·

$

%%%&.

!̄ = max{! ( ) : " { , . . . , }} <

! ( ) # ( $ !̄ )

!"!!!!!!,

21

High controllability and controllers positioning

! "

"

! ( ) ! ( " !̄ )

#!#!#"#!,! ( ) !

"!" / ",

22

Examples

2 4 6 8 10 12 14 16 18 2040

30

20

10

0

N 2 4 6 8 10 12 14 16 18 20

40

30

20

10

0

nb

number of subsystems dimension of subsystems

! ( )

! ( )

! ( )

23

Examples

! ( )

! ( )

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 160

50

40

30

20

10

0

10

n

m

24

Examples

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 160

50

40

30

20

10

0

10

n

! ( )

! ( )

m

25

Examples

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 160

50

40

30

20

10

0

10

n

! ( )

! ( )

m

ConclusionsSimilar results for observability

For controllability we need to control a fixed fraction of nodes

The decoupled control strategy works well for graph that are partitionable

The decoupled control strategy admits a decoupled control synthesis

Random positioning works pretty well

Phase transition can be noticed (critical fraction of controlled nodes)

There are a lot of open problems:

Controllability of random and of structured graphs

Performance of random positioning

Phase transition

Different metrics

26

Thank you

27

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