in Sliding Mode Control Arie Levant School of Mathematical - - PowerPoint PPT Presentation

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in Sliding Mode Control Arie Levant School of Mathematical - - PowerPoint PPT Presentation

IEEE CDC 2013 Excerpt from the presentation Fixed and Finite Time Stability in Sliding Mode Control Arie Levant School of Mathematical Sciences, Tel-Aviv University, Israel Homepage: http://www.tau.ac.il/~levant/ 1 Feasibility of


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IEEE CDC 2013

Excerpt from the presentation

Fixed and Finite Time Stability in Sliding Mode Control

Arie Levant

School of Mathematical Sciences, Tel-Aviv University, Israel Homepage: http://www.tau.ac.il/~levant/

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Feasibility of fixed-time stable control-1

x ∈ F(x) is fixed-time or practically fixed-time stable. Proposition. , ∀τ γ > R ∀ > there are , x x , || || x R ≥ , ( ) x F x ∈

  • , such that

|| || || || x x τ ≥ γ

  • .

Take very small τ, and very large R and γ …

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One Euler step can be incomparably larger than the current (arbitrarily large!) distance from the origin. Any small delay (sampling step) is also not allowed.

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τ-solutions (Euler approximations)

x ∈ F(x), x ∈ Rn – Filippov conditions

( ) ( ( ))

k k

x t F x t = ξ ∈

  • (~ sampling)

1

[ , ]

k k

t t t + ∈ ,

1 k k

t t

+

< − ≤ τ

Over any time segment τ-solutions converge to Filippov solutions with

τ →

.

  • Proposition. With any { }

k

t

,

k

t → ∞, τ-solutions of r-sliding

homogeneous controllers, linear asymptotically stable controllers, etc. converge into small vicinity of 0.

|| || || || / || || ( ) x R x x O ≥ ⇒ τ = τ

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Feasibility of fixed-time stable control-2

x ∈ F(x) is fixed-time or practically fixed-time stable.

Let

( )

enter

T R = sup of the times needed for the solutions to enter || || x R ≤

. ⇒ lim

( )

enter R

T R

→∞

∃ ≥ Usually lim ( )

enter R

T R

→∞

= (Lyap. FxTS functions, uniform

differentiators, homogeneity at infinity, etc.)

  • Theorem. lim

( )

enter R

T R

→∞

= . For any τ > 0 for any large initial conditions there are τ-solutions which escape to infinity faster than any exponent.

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Simulation example

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Classical scalar fixed-time stable system

1/3 3

x u x x = = − −

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Fixed-time stabilization

Initial values 20 x = ,

3

10− τ = Accuracy:

5

| | 1.12 10 x

≤ ⋅ ,

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Initial value (0) 30 x = ,

3

10− τ = Accuracy:

5

| | 1.12 10 x

≤ ⋅

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Initial value (0) 40 x = ,

3

10− τ = . Overshoot! Accuracy:

5

| | 1.12 10 x

≤ ⋅

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Explosion with (0) 50 x = ,

3 4 5 6 7

10 ,10 ,10 ,10 ,10 .

− − − − −

τ = Results with

3

10− τ = : 2 steps

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Results with

3

10− τ = : 3 steps

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Results with

3

10− τ = : 4 steps

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Results with

3

10− τ = : 5 steps

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Results with

3

10− τ = : 6 steps

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3

10− τ = : OVERFLOW at t = 0.007

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Conclusions

  • Computer realization of fixed-time stable systems over unbounded
  • perational regions is not possible.
  • Such systems are realizable for any bounded region of initial

conditions, provided the sampling/integration step is taken small

  • enough. Sampling step should be very carefully chosen.