Hybrid Systems Course Lyapunov stability...STABILITY OF LINEAR CONTINUOUS SYSTEMS Theorem (necessary...

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Hybrid Systems CourseLyapunov stability

OUTLINE

Focus: stability of an equilibrium point

• continuous systems decribed by ordinary differentialequations (brief review)

• hybrid automata

OUTLINE

Focus: stability of an equilibrium point

• continuous systems decribed by ordinary differentialequations (brief review)

• hybrid automata

ORDINARY DIFFERENTIAL EQUATIONS

An ordinary differential equation is a mathematical model of acontinuous state continuous time system:

X = <n ´ state spacef: <n! <n ´ vector field (assigns a “velocity” vector to each x)

Given an initial value x0 2 X,an execution (solution in the sense of Caratheodory) overthe time interval [0,T) is a function x: [0,T) ! <n such that:

• x(0) = x0

• x is continuous and piecewise differentiable

ODE SOLUTION: WELL-POSEDNESS

Theorem [global existence and uniqueness non-blocking,deterministic, non-Zeno]If f: <n! <n is globally Lipschitz continuous, then 8 x0 thereexists a single solution with x(0)=x0 defined on [0,1).

STABILITY OF CONTINUOUS SYSTEMS

with f: <n! <n globally Lipschitz continuous

Definition (equilibrium):xe 2 <n for which f(xe)=0

Remark: {xe} is an invariant set

Definition (stable equilibrium):

Graphically:

δxe

equilibrium motion

perturbed motion

small perturbations lead to small changes in behavior

execution startingfrom x(0)=x0

Definition (asymptotically stable equilibrium):

and can be chosen so that

Graphically:

δxe

equilibrium motion

perturbed motion

small perturbations lead to small changes in behaviorand are re-absorbed, in the long run

Definition (asymptotically stable equilibrium):

and can be chosen so that

Graphically:

small perturbations lead to small changes in behaviorand are re-absorbed, in the long run

δxe

EXAMPLE: PENDULUM

m

l

frictioncoefficient (α)

EXAMPLE: PENDULUM

unstable equilibrium

m

EXAMPLE: PENDULUM

as. stable equilibriumm

EXAMPLE: PENDULUM

m

l

Let xe be asymptotically stable.

Definition (domain of attraction):The domain of attraction of xe is the set of x0 such that

Definition (globally asymptotically stable equilibrium):xe is globally asymptotically stable (GAS) if its domain ofattraction is the whole state space <n

execution startingfrom x(0)=x0

EXAMPLE: PENDULUM

as. stable equilibrium

small perturbations areabsorbed, not allperturbations not GAS

m

m

Let xe be asymptotically stable.

Definition (exponential stability):xe is exponentially stable if 9 , , >0 such that

STABILITY OF CONTINUOUS SYSTEMS

with f: <n! <n globally Lipschitz continuous

Definition (equilibrium):xe 2 <n for which f(xe)=0

Without loss of generality we suppose that

xe = 0if not, then z := x -xe! dz/dt = g(z), g(z) := f(z+xe) (g(0) = 0)

STABILITY OF CONTINUOUS SYSTEMS

with f: <n! <n globally Lipschitz continuous

How to prove stability?find a function V: <n! < such that

V(0) = 0 and V(x) >0, for all x 0V(x) is decreasing along the executions of the system

V(x) = 3

V(x) = 2

x(t)

STABILITY OF CONTINUOUS SYSTEMS

execution x(t)

candidate function V(x)

behavior of V along theexecution x(t): V(t): = V(x(t))

Advantage with respect to exhaustive check of all executions?

with f: <n! <n globally Lipschitz continuous

V: <n! < continuously differentiable (C1) function

Rate of change of V along the execution of the ODE system:

(Lie derivative of V with respect to f)

STABILITY OF CONTINUOUS SYSTEMS

gradient vector

with f: <n! <n globally Lipschitz continuous

V: <n! < continuously differentiable (C1) function

Rate of change of V along the execution of the ODE system:

(Lie derivative of V with respect to f)

STABILITY OF CONTINUOUS SYSTEMS

gradient vector

No need to solve the ODE for evaluating if V(x) decreasesalong the executions of the system

LYAPUNOV STABILITY

Theorem (Lyapunov stability Theorem):Let xe = 0 be an equilibrium for the system and D½ <n an open

set containing xe = 0.If V: D! < is a C1 function such that

Then, xe is stable.

V positive definite on D

V non increasing alongsystem executions in D(negative semidefinite)

EXAMPLE: PENDULUM

m

l

frictioncoefficient (α)

energy function

xe stable

LYAPUNOV STABILITY

Theorem (Lyapunov stability Theorem):Let xe = 0 be an equilibrium for the system and D½ <n an open

set containing xe = 0.If V: D! < is a C1 function such that

Then, xe is stable.

If it holds also that

Then, xe is asymptotically stable (AS)

LYAPUNOV GAS THEOREM

Theorem (Barbashin-Krasovski Theorem):Let xe = 0 be an equilibrium for the system.

If V: <n! < is a C1 function such that

Then, xe is globally asymptotically stable (GAS).

V positive definite on <n

V decreasing alongsystem executions in <n

(negative definite)

V radially unbounded

STABILITY OF LINEAR CONTINUOUS SYSTEMS

• xe = 0 is an equilibrium for the system

• the elements of matrix eAt are linear combinations of tKei(A)t,k=0,…,hi, i=1,2,…,n

STABILITY OF LINEAR CONTINUOUS SYSTEMS

• xe = 0 is an equilibrium for the system

• xe =0 is asymptotically stable if and only if A is Hurwitz (alleigenvalues with real part <0)

• asymptotic stability GAS

STABILITY OF LINEAR CONTINUOUS SYSTEMS

• xe = 0 is an equilibrium for the system

• xe =0 is asymptotically stable if and only if A is Hurwitz (alleigenvalues with real part <0)

• asymptotic stability GAS

Alternative characterization…

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (necessary and sufficient condition):

The equilibrium point xe =0 is asymptotically stable if and onlyif for all matrices Q = QT positive definite (Q>0) the

ATP+PA = -Q

has a unique solution P=PT >0.

Lyapunov equation

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (necessary and sufficient condition):

The equilibrium point xe =0 is asymptotically stable if and onlyif for all matrices Q = QT positive definite (Q>0) the

ATP+PA = -Q

has a unique solution P=PT >0.

Remarks:Q positive definite (Q>0) iff xTQx >0 for all x 0Q positive semidefinite (Q¸ 0) iff xTQx ¸ 0 for all x andxT Q x = 0 for some x 0

Lyapunov equation

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (necessary and sufficient condition):

The equilibrium point xe =0 is asymptotically stable if and onlyif for all matrices Q = QT positive definite (Q>0) the

ATP+PA = -Q

has a unique solution P=PT >0.

Proof.

(if) V(x) =xT P x is a Lyapunov function

Lyapunov equation

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (necessary and sufficient condition):

The equilibrium point xe =0 is asymptotically stable if and onlyif for all matrices Q = QT positive definite (Q>0) the

ATP+PA = -Q

has a unique solution P=PT >0.

Proof.

(only if) Consider

Lyapunov equation

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (necessary and sufficient condition):

The equilibrium point xe =0 is asymptotically stable if and onlyif for all matrices Q = QT positive definite (Q>0) the

ATP+PA = -Q

has a unique solution P=PT >0.

Proof.

(only if) Consider

P = PT and P>0 easy to show

P unique can be proven by contradiction

Lyapunov equation

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Remarks: for a linear system

• existence of a (quadratic) Lyapunov function V(x) =xT P x is anecessary and sufficient condition for asymptotic stability

• it is easy to compute a Lyapunov function since the Lyapunovequation

ATP+PA = -Q

is a linear algebraic equation

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (exponential stability):

Let the equilibrium point xe =0 be asymptotically stable. Then,the rate of convergence to xe =0 is exponential:

for all x(0) = x0 2 <n, where 0 2 (0, mini |Re{i(A)}|) and >0is an appropriate constant.

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (exponential stability):

Let the equilibrium point xe =0 be asymptotically stable. Then,the rate of convergence to xe =0 is exponential:

for all x(0) = x0 2 <n, where 0 2 (0, mini |Re{i(A)}|) and >0is an appropriate constant.

Re

Im

o

o

o o

eigenvalues of A

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (exponential stability):

Let the equilibrium point xe =0 be asymptotically stable. Then,the rate of convergence to xe =0 is exponential:

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Proof (exponential stability):

A + 0 I is Hurwitz (eigenvalues are equal to (A) + 0)

Then, there exists P = PT >0 such that

(A + 0I)T P + P (A + 0I) <0

which leads to

x(t)T[AT P + P A]x(t) < - 2 0 x(t)T P x(t)

Define V(x) = xT P x, then

from which

STABILITY OF LINEAR CONTINUOUS SYSTEMS

(cont’d) Proof (exponential stability):

thus finally leading to

STABILITY OF LINEAR CONTINUOUS SYSTEMS

Theorem (exponential stability):

Let the equilibrium point xe =0 be asymptotically stable. Then,the rate of convergence to xe =0 is exponential:

for all x(0) = x0 2 <n, where 0 2 (0, mini |Re{i(A)}|) and >0is an appropriate constant.

Remark:

STABILITY OF LINEAR CONTINUOUS SYSTEMS

• xe = 0 is an equilibrium for the system

• xe =0 is asymptotically stable if and only if A is Hurwitz (alleigenvalues with real part <0)

• asymptotic stability GAS exponential stability GES

OUTLINE

Focus: stability of an equilibrium point

• continuous systems decribed by ordinary differentialequations (brief review)

• hybrid automata

HYBRID AUTOMATA: FORMAL DEFINITION

A hybrid automaton H is a collection

H = (Q,X,f,Init,Dom,E,G,R)• Q = {q1,q2, …} is a set of discrete states (modes)

• X = <n is the continuous state space

• f: Q£ X! <n is a set of vector fields on X

• Init µ Q£ X is a set of initial states

• Dom: Q! 2X assigns to each q2 Q a domain Dom(q) of X

• E µ Q£ Q is a set of transitions (edges)

• G: E! 2X is a set of guards (guard condition)

• R: E£ X! 2X is a set of reset maps

q = q1

q = q2

HYBRID TIME SET

A hybrid time set is a finite or infinite sequence of intervals

= {Ii, i=0,1,…, M } such that

• Ii = [i, i’] for i < M• IM = [M, M’] or IM = [M, M’) if M<1• i’ = i+1

• i · i’

[ ]

[ ]

[ ]

τ0

I0

τ0’

τ1 τ1’I1

I2 τ2 = τ2’

τ3 τ3’I3

t1

t2

t3

t4

t1 Á t2 Á t3 Á t4

time instants in arelinearly ordered

HYBRID TIME SET: LENGTH

Two notions of length for a hybrid time set = {Ii, i=0,1,…, M }:

• Discrete extent:<> = M+1

• Continuous extent:|||| = i=0,1,..,M |i’-i|

number of discrete transitions

total durationof intervals in

<> = 4|||| = 3’ - 0

[ ]

[ ]

[ ]

τ0

I0

τ0’

τ1 τ1’I1

I2 τ2 = τ2’

τ3 τ3’I3

HYBRID TIME SET: CLASSIFICATION

A hybrid time set = {Ii, i=0,1,…, M } is

• Finite: if <> is finite and IM = [M, M’]

• Infinite: if <> is infinite or |||| is infinite

• Zeno: if <> is infinite but |||| is finite

finite infinite

infinite ZenoZeno

HYBRID TRAJECTORY

A hybrid trajectory (, q, x) consists of:

• A hybrid time set = {Ii, i=0,1,…, M }• Two sequences of functions q = {qi(¢), i=0,1,…, M } and x =

{xi(¢), i=0,1,…, M } such that

qi: Ii! Q

xi: Ii! X

HYBRID AUTOMATA: EXECUTION

A hybrid trajectory (, q, x) is an execution (solution) of thehybrid automaton H = (Q,X,f,Init,Dom,E,G,R) if it satisfiesthe following conditions:

• Initial condition: (q0(0), x0(0)) 2 Init

• Continuous evolution:for all i such that i < i’

qi: Ii! Q is constantxi:Ii! X is the solution to the ODE associated with qi(i)xi(t) 2 Dom(qi(i)), t2 [i,i’)

• Discrete evolution:(qi(i’),qi+1(i+1)) 2 E transition is feasiblexi(i’) 2 G((qi(i’),qi+1(i+1))) guard condition satisfiedxi+1(i+1) 2 R((qi(i’),qi+1(i+1)),xi(i’)) reset condition satisfied

HYBRID AUTOMATA: EXECUTION

Well-posedness?

Problems due the hybrid nature:

for some initial state (q,x)• infinite execution of finite duration Zeno• no infinite execution blocking• multiple executions non-deterministic

We denote by

H(q,x) the set of (maximal) executions of H starting from (q,x)

H(q,x)1 the set of infinite executions of H starting from (q,x)

STABILITY OF HYBRID AUTOMATA

H = (Q,X,f,Init,Dom,E,G,R)

Definition (equilibrium):xe =0 2 X is an equilibrium point of H if:• f(q,0) = 0 for all q 2 Q• if ((q,q’)2 E) Æ (02 G((q,q’)) ) R((q,q’),0) = {0}

Remarks:

• discrete transitions are allowed out of (q,0) but only to (q’,0)• if (q,0) 2 Init and (, q, x) is an execution of H starting from

(q,0), then x(t) = 0 for all t2

EXAMPLE: SWITCHED LINEAR SYSTEM

H = (Q,X,f,Init,Dom,E,G,R)

• Q = {q1, q2} X = <2

• f(q1,x) = A1x and f(q2,x) = A2x with:

• Init = Q £ {x2 X: ||x|| >0}

• Dom(q1) = {x2 X: x1x2 · 0} Dom(q2) = {x2 X: x1x2 ¸ 0}

• E = {(q1,q2),(q2,q1)}• G((q1,q2)) = {x2 X: x1x2 ¸ 0} G((q2,q1)) = {x2 X: x1x2 · 0}

• R((q1,q2),x) = R((q2,q1),x) = {x}

x1

x2

EXAMPLE: SWITCHED LINEAR SYSTEM

EXAMPLE: SWITCHED LINEAR SYSTEM

H = (Q,X,f,Init,Dom,E,G,R)

• Q = {q1, q2} X = <2

• f(q1,x) = A1x and f(q2,x) = A2x with:

• Init = Q £ {x2 X: ||x|| >0}

• Dom(q1) = {x2 X: x1x2 · 0} Dom(q2) = {x2 X: x1x2 ¸ 0}

• E = {(q1,q2),(q2,q1)}• G((q1,q2)) = {x2 X: x1x2 ¸ 0} G((q2,q1)) = {x2 X: x1x2 · 0}

• R((q1,q2),x) = R((q2,q1),x) = {x}

xe = 0 is an equilibrium: f(q,0) = 0 & R((q,q’),0) = {0}

H = (Q,X,f,Init,Dom,E,G,R)

Definition (stable equilibrium):Let xe = 0 2 X be an equilibrium point of H. xe = 0 is stable if

STABILITY OF HYBRID AUTOMATA

set of (maximal) executionsstarting from (q0, x0) 2 Init

H = (Q,X,f,Init,Dom,E,G,R)

Definition (stable equilibrium):Let xe = 0 2 X be an equilibrium point of H. xe = 0 is stable if

Remark:

• Stability does not imply convergence

• To analyse convergence, only infinite executions should beconsidered

STABILITY OF HYBRID AUTOMATA

set of (maximal) executionsstarting from (q0, x0) 2 Init

H = (Q,X,f,Init,Dom,E,G,R)

Definition (stable equilibrium):Let xe = 0 2 X be an equilibrium point of H. xe = 0 is stable if

Definition (asymptotically stable equilibrium):Let xe = 0 2 X be an equilibrium point of H. xe = 0 is asymptotically

stable if it is stable and >0 that can be chosen so that

STABILITY OF HYBRID AUTOMATA

set of (maximal) executionsstarting from (q0, x0) 2 Init

set of infinite executionsstarting from (q0, x0) 2 Init

1 := i(i’-i)continuous extent1 <1 if Zeno

H = (Q,X,f,Init,Dom,E,G,R)

Definition (stable equilibrium):Let xe = 0 2 X be an equilibrium point of H. xe = 0 is stable if

Question:

xe = 0 stable equilibrium for each continuous systemdx/dt = f(q,x) implies that xe = 0 stable equilibrium for H?

STABILITY OF HYBRID AUTOMATA

EXAMPLE: SWITCHED LINEAR SYSTEM

H = (Q,X,f,Init,Dom,E,G,R)

• Q = {q1, q2} X = <2

• f(q1,x) = A1x and f(q2,x) = A2x with:

• Init = Q £ {x2 X: ||x|| >0}

• Dom(q1) = {x2 X: x1x2 · 0} Dom(q2) = {x2 X: x1x2 ¸ 0}

• E = {(q1,q2),(q2,q1)}• G((q1,q2)) = {x2 X: x1x2 ¸ 0} G((q2,q1)) = {x2 X: x1x2 · 0}

• R((q1,q2),x) = R((q2,q1),x) = {x}

xe = 0 is an equilibrium: f(q,0) = 0 & R((q,q’),0) = {0}

x1

x2

EXAMPLE: SWITCHED LINEAR SYSTEM

EXAMPLE: SWITCHED LINEAR SYSTEM

Swiching between asymptotically stable linear systems.

q1: quadrants 2 and 4q2: quadrants 1 and 3

Switching between asymptotically stable linear systems, butxe = 0 unstable equilibrium of H

q1

q1

q2

q2

EXAMPLE: SWITCHED LINEAR SYSTEM

||x(i+1)|| > ||x(i)||

overshootssum up

EXAMPLE: SWITCHED LINEAR SYSTEM

q1: quadrants 1 and 3q2: quadrants 2 and 4

q1

q1

q2

q2

EXAMPLE: SWITCHED LINEAR SYSTEM

||x(i+1)|| < ||x(i)|||

EXAMPLE: SWITCHED LINEAR SYSTEM

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Theorem (Lyapunov stability):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8 (q,q’)2 E, and

D½ X=<n an open set containing xe = 0.Consider V: Q£ D! < is a C1 function in x such that for all q 2 Q:

If for all (, q, x) 2 H(q0,x0) with (q0,x0) 2 Init Å (Q£ D), and all q’2 Q, thesequence {V(q(i),x(i)): q(i) =q’} is non-increasing (or empty),

then, xe = 0 is a stable equilibrium of H.

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Theorem (Lyapunov stability):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8 (q,q’)2 E, and

D½ X=<n an open set containing xe = 0.Consider V: Q£ D! < is a C1 function in x such that for all q 2 Q:

If for all (, q, x) 2 H(q0,x0) with (q0,x0) 2 Init Å (Q£ D), and all q’2 Q, thesequence {V(q(i),x(i)): q(i) =q’} is non-increasing (or empty),

then, xe = 0 is a stable equilibrium of H.

V(q,x) Lyapunov functionfor continuous system q) xe =0 is stableequilibrium for system q

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Theorem (Lyapunov stability):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8 (q,q’)2 E, and

D½ X=<n an open set containing xe = 0.Consider V: Q£ D! < is a C1 function in x such that for all q 2 Q:

If for all (, q, x) 2 H(q0,x0) with (q0,x0) 2 Init Å (Q£ D), and all q’2 Q,the sequence {V(q(i),x(i)): q(i) =q’} is non-increasing (or empty),

then, xe = 0 is a stable equilibrium of H.

V(q,x) Lyapunov functionfor continuous system q) xe =0 is stableequilibrium for system q

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Sketch of the proof.

V(q(t),x(t))V(q1,x(t))

[ ][ ][ ][q(t)= q1 q(t)= q1V(q2,x(t))

0 0’=1 1’=2 2’=3

Lyapunov function forsystem q1! decreaseswhen q(t) = q1, but canincrease when q(t) q1

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Sketch of the proof.

V(q(t),x(t))V(q1,x(t))

[ ]0 0’=1

[ ][ ]1’=2 2’=3

[q(t)= q1 q(t)= q1

{V(q1,x(i))}non-increasing

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Sketch of the proof.

V(q(t),x(t))V(q1,x(t))

[ ]0 0’=1

[ ][ ]1’=2 2’=3

[q(t)= q1 q(t)= q1

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

V(q(t),x(t)) Lyapunov-like function

H = (Q,X,f,Init,Dom,E,G,R)

• Q = {q1, q2} X = <2

• f(q1,x) = A1x and f(q2,x) = A2x with:

• Init = Q £ {x2 X: ||x|| >0}

• Dom(q1) = {x2 X: Cx ¸ 0} Dom(q2) = {x2 X: Cx · 0}

• E = {(q1,q2),(q2,q1)}• G((q1,q2)) = {x2 X: Cx · 0} G((q2,q1)) = {x2 X: Cx ¸ 0}, CT2 <2

• R((q1,q2),x) = R((q2,q1),x) = {x}

EXAMPLE: SWITCHED LINEAR SYSTEM

H = (Q,X,f,Init,Dom,E,G,R)

q1q2

EXAMPLE: SWITCHED LINEAR SYSTEM

x1

x2

EXAMPLE: SWITCHED LINEAR SYSTEM

Cx = 0

Proof that xe = 0 is a stable equilibrium of H for any CT2 <2 :

• xe = 0 is an equilibrium: f(q1,0) = f(q2,0) = 0

R((q1,q2),0) = R((q2,q1),0) = {0}

EXAMPLE: SWITCHED LINEAR SYSTEM

Proof that xe = 0 is a stable equilibrium of H for any CT2 <2 :

• xe = 0 is an equilibrium: f(q1,0) = f(q2,0) = 0

R((q1,q2),0) = R((q2,q1),0) = {0}

• xe = 0 is stable:

consider the candidate Lyapunov-like function:

V(qi,x) = xT Pi x,

where Pi =PiT >0 solution to Ai

T Pi + Pi Ai = - I

(V(qi,x) is a Lyapunov function for the asymptotically stablelinear system qi)

In each discrete state, the continuous system is as. stable.

EXAMPLE: SWITCHED LINEAR SYSTEM

Proof that xe = 0 is a stable equilibrium of H for any CT2 <2:

• xe = 0 is an equilibrium: f(q1,0) = f(q2,0) = 0

R((q1,q2),0) = R((q2,q1),0) = {0}

• xe = 0 is stable:

consider the candidate Lyapunov-like function:

V(qi,x) = xT Pi x,

where Pi =PiT >0 solution to Ai

T Pi + Pi Ai = - I

EXAMPLE: SWITCHED LINEAR SYSTEM

Test for non-increasing sequence condition

Let q(i)=q1 and x(i)=z.

EXAMPLE: SWITCHED LINEAR SYSTEM

Cx = 0

zi

Test for non-increasing sequence condition

Since V(q1,x(t)) is not increasing during [i,i’], then, when x(t)intersects the switching line at i’, it does at z with 2 (0,1],hence ||x(i+1)|| = ||x(i’)|| · ||x(i)||. Let q(i+1)=q2

Cx = 0

-z

i

EXAMPLE: SWITCHED LINEAR SYSTEM

i’=i+1

z

Test for non-increasing sequence condition

Since V(q2,x(t)) is decreasing during [i+1,i+1’], then, when x(t)intersects the switching line at i+1’,||x(i+2)|| = ||x(i+1’)|| · ||x(i+1)|| · ||x(i)||

Cx = 0

-z

i

i’=i+1

i+2

EXAMPLE: SWITCHED LINEAR SYSTEM

z

Test for non-increasing sequence conditionFrom this, it follows that V(q1,x(i+2)) · V(q1,x(i))

Cx = 0

-z

i

i’=i+1

i+2

EXAMPLE: SWITCHED LINEAR SYSTEM

z

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Drawbacks of the approach based on Lyapunov-like functions:

• In general, it is hard to find a Lyapunov-like function

• The sequence {V(q(i),x(i)): q(i) =q’} must be evaluated, whichmay require solving the ODEs

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Corollary (common Lyapunov function):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8

(q,q’)2 E, and D½ X=<n an open set containing xe = 0.

If V: D! < is a C1 function such that for all q 2 Q:

then, xe = 0 is a stable equilibrium of H.

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Corollary (common Lyapunov function):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8

(q,q’)2 E, and D½ X=<n an open set containing xe = 0.

If V: D! < is a C1 function such that for all q 2 Q:

then, xe = 0 is a stable equilibrium of H.

independent of q

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Corollary (common Lyapunov function):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8

(q,q’)2 E, and D½ X=<n an open set containing xe = 0.

If V: D! < is a C1 function such that for all q 2 Q:

then, xe = 0 is a stable equilibrium of H.

V(x) common Lyapunovfunction for all systems q

LYAPUNOV STABILITY

H = (Q,X,f,Init,Dom,E,G,R)

Corollary (common Lyapunov function):Let xe = 0 be an equilibrium for H with R((q,q’),x) = {x}, 8

(q,q’)2 E, and D½ X=<n an open set containing xe = 0.

If V: D! < is a C1 function such that for all q 2 Q:

then, xe = 0 is a stable equilibrium of H.

Proof: Define W(q,x) = V(x), 8 q 2 Q and apply the previous theorem

V(x) common Lyapunovfunction for all systems q

t

))(( txVsame V function+ identity reset map

COMPUTATIONAL LYAPUNOV METHODS

HPL = (Q,X,f,Init,Dom,E,G,R)

non-Zeno and such that for all qk2 Q:• f(qk,x) = Ak x

(linear vector fields)• Init ½ [q2 Q {q } £ Dom(q)

(initialization within the domain)• for all x2 X, the set

Jump(qk,x):= {(q’,x’): (qk,q’)2 E, x2G((qk,q’)), x’2R((qk,q’),x)}has cardinality 1 if x 2 Dom(qk), 0 otherwise(discrete transitions occur only from the boundary of the domains)

• (q’,x’) 2 Jump(qk,x)! x’2 Dom(q’) and x’ = x(trivial reset for x)

COMPUTATIONAL LYAPUNOV METHODS

HPL = (Q,X,f,Init,Dom,E,G,R)

non-Zeno and such that for all qk2 Q:• f(qk,x) = Ak x

(linear vector fields)• Init ½ [q2 Q {q } £ Dom(q)

(initialization within the domain)• for all x2 X, the set

Jump(qk,x):= {(q’,x’): (qk,q’)2 E, x2G((qk,q’)), x’2R((qk,q’),x)}has cardinality 1 if x 2 Dom(qk), 0 otherwise(discrete transitions occur only from the boundary of the domains)

• (q’,x’) 2 Jump(qk,x)! x’2 Dom(q’) and x’ = x(trivial reset for x)

For this class of (non-blocking, deterministic) Piecewise Linear hybridautomata computationally attractive methods exist to construct theLyapunov-like function

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (globally quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists P=PT >0 such thatAk

T P+ PAk < 0, 8 k

Then, xe = 0 is asymptotically stable.

Remark:

V(x)=xTPx is a common Lyapunov function xe = 0 is stable

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

Proof (showing exponential stability):There exists >0 such that Ak

T P+ PAk + I · 0, 8 k

There exists a unique, infinite, non-Zeno execution (,q,x) forevery initial state with x: ! <n satisfying

where k: ! [0,1] is such that k k(t)=1, t2 [i,i’].

Let V(x) = xT Px. Then, for t2 [i,i’).

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

Proof. (cont’d)Since min ||x||2 · V(x) · max ||x||2, then

and, hence,

which leads to

Then,

Since 1 =1 (non-Zeno), then ||x(t)|| goes to zeroexponentially as t! 1

min and max eigenvalues of P

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

q1q2

conditions of the theorem satisfied with P = I

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

q1q2

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (globally quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists P=PT >0 such thatAk

T P+ PAk < 0, 8 k

Then, xe = 0 is asymptotically stable.

Remark:

A set of LMIs to solve. This problem can be reformulated as aconvex optimization problem. Efficient solvers exist.

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

Suppose that Ak , k=1,2,…,N, are Hurwitz matrices.

Then, the set of linear matrix inequalities

AkT P+ PAk < 0, k=1,2,…,N,

where P is positive definite symmetric is not feasible if andonly if there exist positive definite symmetric matrices Rk,k=1,2,…,N, such that

Proof. Based on results in convex analysis

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

q1q2

stable node stable focus

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

q1q2

no globally quadratic Lyapunov function exists although xe = 0 stableequilibrium

stable node stable focus

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

• Idea:consider different quadratic Lyapunov functions on eachdomain and glue them together so as to provide a (non-quadratic) Lyapunov function for H that is continuous at theswitching times

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

• Idea:consider different quadratic Lyapunov functions on eachdomain and glue them together so as to provide a (non-quadratic) Lyapunov function for H that is continuous at theswitching times

• Developed for piecewise linear systems with structureddomain and reset

• LMIs characterization

COMPUTATIONAL LYAPUNOV METHODS

HPL = (Q,X,f,Init,Dom,E,G,R)

non-Zeno and such that for all qk2 Q:• f(qk,x) = Ak x

(linear vector fields)• Init ½ [q2 Q {q } £ Dom(q)

(initialization within the domain)• for all x2 X, the set

Jump(qk,x):= {(q’,x’): (qk,q’)2 E, x2G((qk,q’)), x’2R((qk,q’),x)}has cardinality 1 if x 2 Dom(q), 0 otherwise(discrete transitions occur only from the boundary of the domains)

• (q’,x’) 2 Jump(qk,x)! x’2 Dom(q’) and x’ = x(trivial reset for x)

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

satisfies the following additional assumptions:• Dom(q) = {x 2 X: Eq1x ¸ 0, Eq2 x ¸ 0, … , Eqn x¸ 0}

(each domain is a polygon)Eq = [Eq1

T Eq2T … Eqn

T] T 2 <n£ n defines the domain.

• (q’,x’) 2 Jump(q,x) Fq’x = Fqx, q’q, x’=x(matching condition at the boundaries of the domain)

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (piecewise quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists Uk=UkT, Wk=Wk

T, with all non-negative elements and

M=MT, such that Pk=FkTMFk satisfies

AkT Pk+ PAk + Ek

TUkEk < 0

Pk – EkTWkEk > 0

Then, xe = 0 is asymptotically stable.

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (piecewise quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists Uk=UkT, Wk=Wk

T, with all non-negative elements and

M=MT, such that Pk=FkTMFk satisfies

AkT Pk+ PAk + Ek

TUkEk < 0

Pk – EkTWkEk > 0

Then, xe = 0 is asymptotically stable.

Proof based on the fact that V(x)=xTPkx, xDom(qk) is aLyapunov-like function for HPL, strictly decreasing along itsexecutions

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (piecewise quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists Uk=UkT, Wk=Wk

T, with all non-negative elements and

M=MT, such that Pk=FkTMFk satisfies

AkT Pk+ PAk + Ek

TUkEk < 0

Pk – EkTWkEk > 0 Pk positive definite within Dom(k)

Then, xe = 0 is asymptotically stable.

Proof based on the fact that V(x)=xTPkx, xDom(qk) is aLyapunov-like function for HPL, strictly decreasing along itsexecutions

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (piecewise quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists Uk=UkT, Wk=Wk

T, with all non-negative elements and

M=MT, such that Pk=FkTMFk satisfies

AkT Pk+ PAk + Ek

TUkEk < 0 AkT Pk+ PAk < 0 within Dom(k)

Pk – EkTWkEk > 0 Pk positive definite within Dom(k)

Then, xe = 0 is asymptotically stable.

Proof based on the fact that V(x)=xTPkx, xDom(qk) is aLyapunov-like function for HPL, strictly decreasing along itsexecutions

PIECEWISE QUADRATIC LYAPUNOV FUNCTION

HPL = (Q,X,f,Init,Dom,E,G,R)

Theorem (piecewise quadratic Lyapunov function):

Let xe = 0 be an equilibrium for HPL.

If there exists Uk=UkT, Wk=Wk

T, with all non-negative elements and

M=MT, such that Pk=FkTMFk satisfies

AkT Pk+ PAk + Ek

TUkEk < 0

Pk – EkTWkEk > 0

Then, xe = 0 is asymptotically stable.

Proof based on the fact that V(x)=xTPkx, xDom(qk) is aLyapunov-like function for HPL, strictly decreasing along itsexecutions

continuitity of V(x)

GLOBALLY QUADRATIC LYAPUNOV FUNCTION

q1q2

level curves of thepiecewise quadraticLyapunov function(red lines)

phase plot of somecontinuous statetrajectories(blue lines)

REFERENCES

• H.K. Khalil.Nonlinear Systems.Prentice Hall, 1996.

• S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishnan.Linear Matrix Inequalities in System and Control Theory.SIAM, 1994.

• M. Branicky.Multiple Lyapunov functions and other analysis tools for switched andhybrid systems.IEEE Trans. on Automatic Control, 43(4):475-482, 1998.

• H. Ye, A. Michel, and L. Hou.Stability theory for hybrid dynamical systems.IEEE Transactions on Automatic Control, 43(4):461-474, 1998.

• M. Johansson and A. Rantzer.Computation of piecewise quadratic Lyapunov function for hybridsystems.IEEE Transactions on Automatic Control, 43(4):555-559, 1998.

• R.A. Decarlo, M.S. Branicky, S. Petterson, and B. Lennartson.Perspectives and results on the stability and stabilization of hybridsystems.Proceedings of the IEEE, 88(7):1069-1082, 2000.