Rated Stability - lee.uerj.brvss2020/Homepage-Summer-School/Lectures/VSS-2019... · (Erugin 1951,...
Transcript of Rated Stability - lee.uerj.brvss2020/Homepage-Summer-School/Lectures/VSS-2019... · (Erugin 1951,...
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Rated Stability
L. Fridman
UNAM
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Outline
1 IntroductionHistorical RemarksModel of Dynamical System
2 Stability NotionsUnrated StabilityRated StabilityNon-Asymptotic Stability
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A.M. Lyapunov (1857-1918) and the first page of his thesis
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Dynamic Systems and Stability
Pendulum Equation
Consider the pendulum equation
θ(t) + k θ(t) +g
rsin (θ(t)) = 0
where
θ – an inclination angle,
k – a friction coefficient
r – a length of pendulum,
g – the gravitationconstant.
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Outline
1 IntroductionHistorical RemarksModel of Dynamical System
2 Stability NotionsUnrated StabilityRated StabilityNon-Asymptotic Stability
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Historical Remarks
Unrated Stability
Lyapunov Stability, Asymptotic Stability(Lyapunov 1892, Zubov 1957, Krasovskii 1959, LaSalle & Lefschetz 1960,Hahn 1961, Roxin 1965 etc)
Rated Stability
Exponential, Finite-time and Fixed-time Stability(Erugin 1951, Zubov 1957, Hahn 1961, Roxin 1966, Demidovich 1974,Bhat & Bernstein 2000, Orlov 2005, Levant 2005, Moulay & Perruquetti2005, Andrieu et al 2008,Cuz, Moreno, Fridman 2010, Polyakov 2012,...)
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Historical Remarks
Unrated Stability
Lyapunov Stability, Asymptotic Stability(Lyapunov 1892, Zubov 1957, Krasovskii 1959, LaSalle & Lefschetz 1960,Hahn 1961, Roxin 1965 etc)
Rated Stability
Exponential, Finite-time and Fixed-time Stability(Erugin 1951, Zubov 1957, Hahn 1961, Roxin 1966, Demidovich 1974,Bhat & Bernstein 2000, Orlov 2005, Levant 2005, Moulay & Perruquetti2005, Andrieu et al 2008,Cuz, Moreno, Fridman 2010, Polyakov 2012,...)
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Outline
1 IntroductionHistorical RemarksModel of Dynamical System
2 Stability NotionsUnrated StabilityRated StabilityNon-Asymptotic Stability
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System Description
Model of the System
Consider the differential inclusion
x(t) ∈ F (t, x(t)), t ∈ R; (Sys)
x(t0) = x0, x0 ∈ R (IC)
Assumption
0 ∈ F (t, 0) for t ∈ R
Notation
Φ(t, t0, x0)– Set of all solutions of the Cauchy problem (Sys);
x(t, t0, x0) ∈ Φ(t, t0, x0)– a solution of (Sys)-(IC).
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System Description
Model of the System
Consider the differential inclusion
x(t) ∈ F (t, x(t)), t ∈ R; (Sys)
x(t0) = x0, x0 ∈ R (IC)
Assumption
0 ∈ F (t, 0) for t ∈ R
Notation
Φ(t, t0, x0)– Set of all solutions of the Cauchy problem (Sys);
x(t, t0, x0) ∈ Φ(t, t0, x0)– a solution of (Sys)-(IC).
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Weak Stability
Example
Weakly stable system{x1 = x2
x2 ∈ −(k1sign[x1] u k2sign[x2]
),, xi ∈ R,
2 cases
If k1 > k2 > 0 → x1 = 0, x2 = 0 is finite stable equilibrium point
If k2 > |k1| → x1(t) = constant, x2 = 0 is a solution.
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Weak Stability
Example
Weakly stable system{x1 = x2
x2 ∈ −(k1sign[x1] u k2sign[x2]
),, xi ∈ R,
2 cases
If k1 > k2 > 0 → x1 = 0, x2 = 0 is finite stable equilibrium point
If k2 > |k1| → x1(t) = constant, x2 = 0 is a solution.
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Outline
1 IntroductionHistorical RemarksModel of Dynamical System
2 Stability NotionsUnrated StabilityRated StabilityNon-Asymptotic Stability
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Lyapunov Stability
Definition (Stability, Lyapunov 1892)
The origin of the system (Sys) is said to be Lyapunov stable if ∀ε ∈ R+
and ∀t0 ∈ R : ∃δ = δ(ε, t0) ∈ R+ such that ∀x0 ∈ B(δ)
1 any solution x(t, t0, x0) of Cauchy problem (Sys)-(IC) exists fort > t0;
2 x(t, t0, x0) ∈ B(ε) for t > t0.
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Uniform Stability and Instability
Definition (Uniform Lyapunov Stability)
If the function δ in Definition of Lyapunov Stability does not depend on t0
then the origin is called uniformly Lyapunov stable.
If x ∈ F (x) is Lyapunov stable, then it is uniform Lyapunov stable
Proposition
If the origin of the system (Sys) is Lyapunov stable then x(t) = 0 is theunique solution of Cauchy problem (Sys)-(IC) with x0 = 0 and t0 ∈ R.
Definition (Instability)
The origin, which does not satisfy any condition from Lyapunov Stabilitydefinition, is called unstable.
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Uniform Stability and Instability
Definition (Uniform Lyapunov Stability)
If the function δ in Definition of Lyapunov Stability does not depend on t0
then the origin is called uniformly Lyapunov stable.
If x ∈ F (x) is Lyapunov stable, then it is uniform Lyapunov stable
Proposition
If the origin of the system (Sys) is Lyapunov stable then x(t) = 0 is theunique solution of Cauchy problem (Sys)-(IC) with x0 = 0 and t0 ∈ R.
Definition (Instability)
The origin, which does not satisfy any condition from Lyapunov Stabilitydefinition, is called unstable.
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Uniform Stability and Instability
Definition (Uniform Lyapunov Stability)
If the function δ in Definition of Lyapunov Stability does not depend on t0
then the origin is called uniformly Lyapunov stable.
If x ∈ F (x) is Lyapunov stable, then it is uniform Lyapunov stable
Proposition
If the origin of the system (Sys) is Lyapunov stable then x(t) = 0 is theunique solution of Cauchy problem (Sys)-(IC) with x0 = 0 and t0 ∈ R.
Definition (Instability)
The origin, which does not satisfy any condition from Lyapunov Stabilitydefinition, is called unstable.
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Uniform Stability and Instability
Definition (Uniform Lyapunov Stability)
If the function δ in Definition of Lyapunov Stability does not depend on t0
then the origin is called uniformly Lyapunov stable.
If x ∈ F (x) is Lyapunov stable, then it is uniform Lyapunov stable
Proposition
If the origin of the system (Sys) is Lyapunov stable then x(t) = 0 is theunique solution of Cauchy problem (Sys)-(IC) with x0 = 0 and t0 ∈ R.
Definition (Instability)
The origin, which does not satisfy any condition from Lyapunov Stabilitydefinition, is called unstable.
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Example (Uniformly Lyapunov Stable System)
{x1 ∈ sign[−x2],x2 ∈ sign[x1]
, x1, x2 ∈ R
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Example (Uniformly Lyapunov Stable System)
No sliding motion{x1= sign[−x2],x2= sign[x1]
, x1, x2 ∈ R
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Example (Uniformly Lyapunov Stable System)
No sliding motion{x1= sign[−x2],x2= sign[x1]
, x1, x2 ∈ R
V = |x1|+ |x2|
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Example (Uniformly Lyapunov Stable System)
No sliding motion{x1= sign[−x2],x2= sign[x1]
, x1, x2 ∈ R
V = |x1|+ |x2|
V = sign(x1)x1 + sign(x2)x2 = 0
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Example (Uniformly Lyapunov Stable System)
No sliding motion{x1= sign[−x2],x2= sign[x1]
, x1, x2 ∈ R
V = |x1|+ |x2|
V = sign(x1)x1 + sign(x2)x2 = 0
Lyapunov Stability
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Definition (Asymptotic attrativity)
The origin of the system (Sys) is said to be asymptotically attractive if∀t0 ∈ R exists a set U(t0) ⊆ Rn : U(t0) \ 0 is non-empty and ∀x0 ∈ U(t0)
any solution x(t, t0, x0) of Cauchy problem (Sys)-(IC) exists fort > t0;
limt→+∞
‖x(t, t0, x0)‖ = 0.
The set U(t0) is called attraction domain.
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Definition (Asymptotic stability)
The origin of the system (Sys) is said to be asymptotically stable if it is
Lyapunov stable;
asymptotically attractive with an attraction domain U(t0) ⊆ Rn suchthat 0 ∈ int(U(t0)) for all t0 ∈ R.
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Asymptotic attractivity may not imply Asymptotic Stability
Example (R.E. Vinograd 1957)
x1 =x2
1 (x2 − x1) + x52(
x21 + x2
2
) (1 +
(x2
1 + x22
)2)
and
x2 =x2
2 (x2 − 2x1)(x2
1 + x22
) (1 +
(x2
1 + x22
)2)
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Definition (Uniform Asymptotic Attractivity)
The origin of the system (Sys) is said to be uniformly asymptoticallyattractive
if it is asymptotically attractive with a time-invariant attractiondomain U ⊆ Rn;
∀R ∈ R+, ∀ε ∈ R+ there exists T = T (R, ε) ∈ R+ such that theinclusions x0 ∈ B(R) ∩ U and t0 ∈ R imply x(t, t0, x0) ∈ B(ε) fort > t0 + T .
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Uniform Asymptotic Stability
Definition (Uniform asymptotic stability)
The origin of the system (Sys) is said to be uniformly asymptoticallystable if it is uniformly Lyapunov stable and uniformly asymptoticallyattractive with an attraction domain U ⊆ Rn : 0 ∈ int(U).
Proposition (Clarke, Ledyaev, Stern 1998)
Let a set-valued function F : Rn → Rn be defined andupper-semicontinuous in Rn. Let F (x) be nonempty, compact and convexfor any x ∈ Rn.If the origin of the system
x ∈ F (x)
is asymptotically stable then it is uniformly asymptotically stable.
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Uniform Asymptotic Stability
Definition (Uniform asymptotic stability)
The origin of the system (Sys) is said to be uniformly asymptoticallystable if it is uniformly Lyapunov stable and uniformly asymptoticallyattractive with an attraction domain U ⊆ Rn : 0 ∈ int(U).
Proposition (Clarke, Ledyaev, Stern 1998)
Let a set-valued function F : Rn → Rn be defined andupper-semicontinuous in Rn. Let F (x) be nonempty, compact and convexfor any x ∈ Rn.If the origin of the system
x ∈ F (x)
is asymptotically stable then it is uniformly asymptotically stable.
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Outline
1 IntroductionHistorical RemarksModel of Dynamical System
2 Stability NotionsUnrated StabilityRated StabilityNon-Asymptotic Stability
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Definition (Exponential stability)
The origin of the system (Sys) is said to be exponentially stable if thereexist an attraction domain U ⊆ Rn : 0 ∈ int(U) and numbers C , r ∈ R+
such that‖x(t, t0, x0)‖ ≤ C‖x0‖e−r(t−t0), t > t0.
for t0 ∈ R and x0 ∈ U.
The theory of Linear Control Systems deals with exponential stability
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Example (Linear Variable Structure System)
x = −(2− sign[sin(x)])x , x ∈ R, x(t0) = x0
‖x(t, t0, x0‖ ≤ |x0|e−(t−t0), t > t0
4 6 8 10
0
0.5
1
t
‖x(t,t 0,x0‖
‖x(t, 4, 1)‖e−(t−4)
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Example (Homogeneous system)
x = −bxeα; x(0) = x0 0 < α < 1 1
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Example (Homogeneous system)
x = −bxeα; x(0) = x0 0 < α < 1 1
x0 >= 0
⇒ x(t) >= 0 ∀t ∈ [0, t1]
x = −xα
⇒ x(t) =(x1−α
0 − (1− α)t) 1
1−α
x(t) = 0 at t =x1−α
0
1− α
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Example (Homogeneous system)
x = −bxeα; x(0) = x0 0 < α < 1 1
x0 >= 0
⇒ x(t) >= 0 ∀t ∈ [0, t1]
x = −xα
⇒ x(t) =(x1−α
0 − (1− α)t) 1
1−α
x(t) = 0 at t =x1−α
0
1− α
x0 <= 0
⇒ x(t) <= 0 ∀t ∈ [0, t1]
x = (−x)α
⇒ x(t) =((−x0)1−α − (1− α)t
) 11−α
x(t) = 0 at t =(−x0)1−α
1− α
1b·eα = | · |α sign[·]L. Fridman Stability 22 / 34
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Example (Homogeneous system)
x = −bxeα; x(0) = x0 0 < α < 1 1
x0 >= 0
⇒ x(t) >= 0 ∀t ∈ [0, t1]
x = −xα
⇒ x(t) =(x1−α
0 − (1− α)t) 1
1−α
x(t) = 0 at t =x1−α
0
1− α
x0 <= 0
⇒ x(t) <= 0 ∀t ∈ [0, t1]
x = (−x)α
⇒ x(t) =((−x0)1−α − (1− α)t
) 11−α
x(t) = 0 at t =(−x0)1−α
1− α
∴ x(t) = 0 ∀t ≥ |x0|1−α
1− α
1b·eα = | · |α sign[·]L. Fridman Stability 22 / 34
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Mechanical Example
Example (Deceleration of a Cart)
L. Fridman Stability 23 / 34
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Mechanical Example
Example (Deceleration of a Cart)
mx = −kd sign[x ]
m – mass
x – position
kd – coefficients of dryfriction
L. Fridman Stability 23 / 34
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Mechanical Example
Example (Deceleration of a Cart)
mx = −kd sign[x ]
m – mass
x – position
kd – coefficients of dryfriction
x(t) = 0, ∀t ≥ m
kd|x(0)|
L. Fridman Stability 23 / 34
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Mechanical Example
Example (Deceleration of a Cart)
0 1 2 3 4 5
0
2
4
t
x
mx = −kd sign[x ]
m – mass
x – position
kd – coefficients of dryfriction
x(t) = 0, ∀t ≥ m
kd|x(0)|
L. Fridman Stability 23 / 34
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Outline
1 IntroductionHistorical RemarksModel of Dynamical System
2 Stability NotionsUnrated StabilityRated StabilityNon-Asymptotic Stability
L. Fridman Stability 24 / 34
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Finite-time attractivity
Introduce the functional T0 : Wn[t0,+∞) → R+ ∪ {0} by
T0(y(·)) = infτ≥t0:y(τ)=0
τ.
If y(τ) 6= 0 for all t ∈ [t0,+∞) then T0(y(·)) = +∞.Define the settling-time function of the system (Sys) as
T (t0, x0) = supx(t,t0,x0)∈Φ(t0,x0)
T0(x(t, t0, x0))− t0.
Definition (Finite-time attractivity)
The origin of the system (Sys) is said to be finite-time attractive if ∀t0 ∈ R existsa set V(t0) ⊆ Rn : V (t0) \ {0} is non-empty and ∀x0 ∈ V(t0)
any solution x(t, t0, x0) of Cauchy problem (Sys)-(IC) exists for t > t0;
T (t0, x0) < +∞ for x0 ∈ V(t0) and for t0 ∈ R.
The set V(t0) is called finite-time attraction domain.
L. Fridman Stability 25 / 34
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Finite-time attractivity
Introduce the functional T0 : Wn[t0,+∞) → R+ ∪ {0} by
T0(y(·)) = infτ≥t0:y(τ)=0
τ.
If y(τ) 6= 0 for all t ∈ [t0,+∞) then T0(y(·)) = +∞.Define the settling-time function of the system (Sys) as
T (t0, x0) = supx(t,t0,x0)∈Φ(t0,x0)
T0(x(t, t0, x0))− t0.
Definition (Finite-time attractivity)
The origin of the system (Sys) is said to be finite-time attractive if ∀t0 ∈ R existsa set V(t0) ⊆ Rn : V (t0) \ {0} is non-empty and ∀x0 ∈ V(t0)
any solution x(t, t0, x0) of Cauchy problem (Sys)-(IC) exists for t > t0;
T (t0, x0) < +∞ for x0 ∈ V(t0) and for t0 ∈ R.
The set V(t0) is called finite-time attraction domain.
L. Fridman Stability 25 / 34
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Finite-time Stability (Erugin 1991, Zubov 1957, etc)
Definition (Finite-time stability, Roxin 1966)
The origin of the system (Sys) is said to be finite-time stable if it isLyapunov stable and finite-time attractive with an attraction domainV(t0) ⊆ Rn such that 0 ∈ int(V(t0)) for any t0 ∈ R.
Proposition (Bhat & Bernstein 2000)
If the origin of the system (Sys) is finite-time stable then it isasymptotically stable and x(t, t0, x0) = 0 for t > t0 + T0(t0, x0).
L. Fridman Stability 26 / 34
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Finite-time Stability (Erugin 1991, Zubov 1957, etc)
Definition (Finite-time stability, Roxin 1966)
The origin of the system (Sys) is said to be finite-time stable if it isLyapunov stable and finite-time attractive with an attraction domainV(t0) ⊆ Rn such that 0 ∈ int(V(t0)) for any t0 ∈ R.
Proposition (Bhat & Bernstein 2000)
If the origin of the system (Sys) is finite-time stable then it isasymptotically stable and x(t, t0, x0) = 0 for t > t0 + T0(t0, x0).
L. Fridman Stability 26 / 34
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Uniform Finite-time Stability (Roxin 1966, Praly 1997, etc)
Definition (Uniform finite-time attractivity)
The origin of the system (Sys) is said to be uniformly finite-time attractiveif
it is finite-time attractive with a time-invariant attraction domainV ⊆ Rn;
T (t0, x0) is locally bounded on R× V uniformly on t0 ∈ R, i.e.
∀y ∈ V : ∃ε ∈ R+ ⇒ supt0∈R,
x0∈{y}uB(ε)⊂V
T (t0, x0) < +∞.
L. Fridman Stability 27 / 34
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Uniform Finite-time Stability (Roxin 1966, Praly 1997, etc)
Definition (Uniform finite-time stability (Orlov 2005)))
The origin of the system (Sys) is said to be uniformly finite-time stable ifit is uniformly Lyapunov stable and uniformly finite-time attractive with anattraction domain V ⊆ Rn : 0 ∈ int(V).
Example
x ∈ −sign[x ], x ∈ R, T (t0, x0) = |x0|
L. Fridman Stability 27 / 34
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Time invariance does not imply uniformity of FTS
Example (S.P. Bhat & D. Bernstein 2000)
Denote x i0 =(0, −1
i
)T, i = 1, 2, 3, . . .
x i0 → 0 and T (x i0)→ +∞
L. Fridman Stability 28 / 34
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Time invariance does not imply uniformity of FTS
Example (S.P. Bhat & D. Bernstein 2000)
Denote x i0 =(0, −1
i
)T, i = 1, 2, 3, . . .
x i0 → 0 and T (x i0)→ +∞
L. Fridman Stability 28 / 34
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Example
Two uniformly finite-time stable systems Consider two systems2
(I ) x = −bxe12 (1− |x |) ,
(II ) x =
{−bxe
12 for x < 1,
0 for x ≥ 1,
which are uniformly finite-time stable with V = B(1).
T(I )(x0) = ln
(1 + |x0|
12
1− |x0|12
)T(I )(x0)→ +∞ if x0 → ±1
T(II )(x0) = 2|x0|12 .
T(II )(x0)→ 2 if x0 → ±1
2bxe[ρ] = |x |ρ sign[x ]L. Fridman Stability 29 / 34
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Example
Two uniformly finite-time stable systems Consider two systems2
(I ) x = −bxe12 (1− |x |) ,
(II ) x =
{−bxe
12 for x < 1,
0 for x ≥ 1,
which are uniformly finite-time stable with V = B(1).
T(I )(x0) = ln
(1 + |x0|
12
1− |x0|12
)T(I )(x0)→ +∞ if x0 → ±1
T(II )(x0) = 2|x0|12 .
T(II )(x0)→ 2 if x0 → ±1
2bxe[ρ] = |x |ρ sign[x ]L. Fridman Stability 29 / 34
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Mechanical Example
Example (Deceleration of a Cart)
L. Fridman Stability 30 / 34
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Mechanical Example
Example (Deceleration of a Cart)
mx = −(kd + kv x
2)
sign[x ], t > 0
m – mass
x – position
kd , kv – coefficients of dry andviscous friction
L. Fridman Stability 30 / 34
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Mechanical Example
Example (Deceleration of a Cart)
mx = −(kd + kv x
2)
sign[x ], t > 0
m – mass
x – position
kd , kv – coefficients of dry andviscous friction
x(t) = 0, ∀t ≥ Tmax =mπ
2√kdkv
and for any (x0, x0) ∈ R2
L. Fridman Stability 30 / 34
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Mechanical Example
Example (Deceleration of a Cart)
0 0.2 0.4 0.6 0.8 1
0
0.2
0.4
0.6
0.8
1
t
x
x0 = 1 x0 = 10 x0 = 100 x0 = 1000 Tmax mx = −(kd + kv x
2)
sign[x ], t > 0
m – mass
x – position
kd , kv – coefficients of dry andviscous friction
x(t) = 0, ∀t ≥ Tmax =mπ
2√kdkv
and for any (x0, x0) ∈ R2
L. Fridman Stability 30 / 34
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Example
x = −bxe12 − bxe
32 , x(0) = x0 > 0
dx√x (1 + x)
= −dt
z =√x ⇒ x = z2 dx = 2zdz
2
∫dz
1 + z2= −
∫dt
2 arctan√x = C − t, t = 0 ⇒ C = 2 arctan
√x0
2 arctan√x = 2 arctan
√x0 − t, ∀x0, t < π
L. Fridman Stability 31 / 34
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Example
x = −√x −√x3
dx√x (1 + x)
= −dt
z =√x ⇒ x = z2 dx = 2zdz
2
∫dz
1 + z2= −
∫dt
2 arctan√x = C − t, t = 0 ⇒ C = 2 arctan
√x0
2 arctan√x = 2 arctan
√x0 − t, ∀x0, t < π
L. Fridman Stability 31 / 34
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Example
x = −√x −√x3
dx√x (1 + x)
= −dt
z =√x ⇒ x = z2 dx = 2zdz
2
∫dz
1 + z2= −
∫dt
2 arctan√x = C − t, t = 0 ⇒ C = 2 arctan
√x0
2 arctan√x = 2 arctan
√x0 − t, ∀x0, t < π
L. Fridman Stability 31 / 34
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Example
x = −√x −√x3
dx√x (1 + x)
= −dt
z =√x ⇒ x = z2 dx = 2zdz
2
∫dz
1 + z2= −
∫dt
2 arctan√x = C − t, t = 0 ⇒ C = 2 arctan
√x0
2 arctan√x = 2 arctan
√x0 − t, ∀x0, t < π
L. Fridman Stability 31 / 34
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Example
x = −√x −√x3
dx√x (1 + x)
= −dt
z =√x ⇒ x = z2 dx = 2zdz
2
∫dz
1 + z2= −
∫dt
2 arctan√x = C − t, t = 0 ⇒ C = 2 arctan
√x0
2 arctan√x = 2 arctan
√x0 − t, ∀x0, t < π
L. Fridman Stability 31 / 34
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Example
x = −√x −√x3
dx√x (1 + x)
= −dt
z =√x ⇒ x = z2 dx = 2zdz
2
∫dz
1 + z2= −
∫dt
2 arctan√x = C − t, t = 0 ⇒ C = 2 arctan
√x0
2 arctan√x = 2 arctan
√x0 − t, ∀x0, t < π
L. Fridman Stability 31 / 34
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Fixed-time Stability(Balakrishan 1996, Andrieu et al2008,Cruz, Moreno, Fridman 2010,...)
Definition (Fixed-time attractivity)
The origin of the system (Sys) is said to be fixed-time attractive if
it is uniformly finite-time attractive with an attraction domain V;
T (t0, x0) is bounded on R× V, i.e.
∃Tmax ∈ R+ such that T (t0, x0) ≤ Tmax if t0 ∈ R, x0 ∈ V
Definition (Fixed-time stability, Polyakov 2012)
The origin of the system (Sys) is said to be fixed-time stable if it isLyapunov stable and fixed-time attractive with an attraction domainV ⊆ Rn : 0 ∈ int(V).
L. Fridman Stability 32 / 34
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Fixed-time stability ⇒ NON-Asymptotic estimation &control
{x(t) = u(t)x(t) = x0,
x , u ∈ R
L. Fridman Stability 33 / 34
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Fixed-time stability ⇒ NON-Asymptotic estimation &control
{x(t) = u(t)x(t) = x0,
x , u ∈ R
Asymptotic stabilisation:
u(t) = −x(t)
x(t) = e−tx0 → 0 if t → +∞
L. Fridman Stability 33 / 34
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Fixed-time stability ⇒ NON-Asymptotic estimation &control
{x(t) = u(t)x(t) = x0,
x , u ∈ R
Finite-Time stabilisation:
u(t) = −bx(t)e0
x(t) = 0 for t ≥ ‖x0‖
L. Fridman Stability 33 / 34
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Fixed-time stability ⇒ NON-Asymptotic estimation &control
{x(t) = u(t)x(t) = x0,
x , u ∈ R
Fixed-Time stabilisation:
u(t) = −bx(t)e12 − bx(t)e
32
x(t) = 0 for t ≥ π
independently of x0
L. Fridman Stability 33 / 34
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Summary
In general case, attractivity does not imply stability.
Strong stability is more preferable for control applications.
Control theory is mainly interested in rated stability.
L. Fridman Stability 34 / 34