Robust Stabilization of Nonlinear Systems: Sliding Mode Control, Slides of Nonlinear Control Systems

An overview of robust stabilization techniques for nonlinear systems using sliding mode control. The concept of a sliding manifold, the conditions for reaching and maintaining the manifold, and methods for reducing chattering. It also discusses the analysis of the system and the behavior of trajectories inside the positively invariant set.

Typology: Slides

2011/2012

Uploaded on 07/11/2012

dikshan
dikshan 🇮🇳

4.3

(7)

73 documents

1 / 17

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
Nonlinear Systems and Control
Lecture # 32
Robust Stabilization
Sliding Mode Control
p. 1/17
Docsity.com
pf3
pf4
pf5
pf8
pf9
pfa
pfd
pfe
pff

Partial preview of the text

Download Robust Stabilization of Nonlinear Systems: Sliding Mode Control and more Slides Nonlinear Control Systems in PDF only on Docsity!

Nonlinear Systems and Control

Lecture # 32

Robust Stabilization

Sliding Mode Control

Docsity.com

Example

x

1

x

2

x

2

h

x

g

x

u,

g

x

g

0

Sliding Manifold (Surface):

s

a

1

x

1

x

2

s

t

x

1

a

1

x

1

a

1

lim t

→∞

x

1

t

How can we bring the trajectory to the manifold

s

How can we maintain it there?

Docsity.com

s <

u

β

x

V

g

x

s

x

g

x

su

g

x

s

x

g

x

β

x

s

V

g

x

s

x

g

x

̺^

x

β

0

s

g

x

β

0

s

sgn(

s

s >

s <

u

β

x

) sgn(

s

V

g

x

β

0

s

g

0

β

0

s

V

g

0

β

0

V

Docsity.com

V

g

0

β

0

V

dV √

V

g

0

β

0

dt

V

V

(

s

(

t

))

V

(

s

(0))

g

0

β

0

t

V

s

t

V

s

g

0

β

0

t

s

t

s

g

0

β

0

t

s

t

reaches zero in finite time

Once on the surface

s

, the trajectory cannot leave it

Docsity.com

x

1

x

2

x

2

h

x

g

x

β

x

)sgn(

s

x

1

a

1

x

1

s

s

a

1

x

2

h

x

g

x

β

x

)sgn(

s

s

s

g

0

β

0

s

if

β

x

x

β

0

V

1

1 2

x

2 1

V

1

x

1

x

1

a

1

x

2 1

x

1

s

a

1

x

2 1

x

1

c

s

c

and

x

1

c

a

1

x

1

c a

1

s

c

is positively invariant if

a

1

x

2

h

x

g

x

x

over

Docsity.com

x

1

c a

1

s

c

6

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

H

x

1

x

2

s

c/a

1

c

a

1

x

2

h

x

g

x

k

1

< k,

x

u

k

sgn(

s

Docsity.com

Reduce the amplitude of the signum function

s

a

1

x

2

h

x

g

x

u

u

[

a

1

x

2

ˆh

x

)]

ˆg

x

v

s

δ

x

g

x

v

δ

x

a

1

[

g

x

ˆg

x

]

x

2

h

x

g

x

ˆg

x

ˆh

x

δ

x

g

x

x

β

x

x

β

0

v

β

x

) sgn(

s

Docsity.com

Replace the signum function by a high-slope saturationfunction

u

β

x

) sat

s ε

sat(

y

y,

if

y

sgn(

y

if

y

6

y

sgn(

y

6











 −

y

ε

sat

y^ ε

Docsity.com

Inside the boundary layer:

x

1

a

1

x

1

s

s

a

1

x

2

h

x

g

x

β

x

s ε

x

1

x

1

a

1

x

2 1

x

1

ε

< θ <

x

1

x

1

θ

a

1

x

2 1

x

1

ε

θa

1

The trajectories reach the positively invariant set

ε

x

1

ε

θa

1

s

ε

in finite time

Docsity.com

What happens inside

ε

Find the equilibrium points

a

1

x

1

s

x

2

a

1

x

2

h

x

g

x

β

x

s ε

φ

x

1

h

x

a

1

g

x

β

x

x

2

=

x

1

εφ

x

1

Suppose

x

1

εφ

x

1

has an isolated root

¯x

1

εk

1

h

¯x

1

Docsity.com

z

1

a

1

z

1

z

2

z

2

z

g

x

β

x

z

2 ε

z

1

z

1

2

z

2

g

x

β

x

g

0

β

0

V

1 2

z

(^21)

1 2

z

(^22)

V

z

1

a

1

z

1

z

2

z

2

[

z

g

x

β

x

z

2 ε

]

V

a

1

z

(^21)

1

z

1

z

2

2

z

(^22)

g

0

β

0

ε

z

(^22)

Docsity.com

V

a

1

z

(^21)

1

z

1

z

2

2

z

(^22)

g

0

β

0

ε

z

(^22)

V

[

z

1

z

2

]

T

[

a

1

1 2

1

1 2

1

g

0

β

0

ε

2

]

Q

[

z

1

z

2

]

det(

Q

a

1

g

0

β

0

ε

2

1 4

1

2

h

lim t

→∞

x

t

h

lim t

→∞

x

t

[

¯x

1

0

]

Read Section 14.1.

Docsity.com