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Spectral Decomposition of Open
Channel Flow
Xavier Litrico (Cemagref, UMR G-EAU, Montpellier)
with Vincent Fromion (INRA MIG, Jouy-en-Josas)
Motivation
• Agriculture = 70% of fresh water world consumption • Irrigated agriculture = 17% of agricultural area, 40% of food
production• Water for agriculture
• Large operational losses: 20% to 70%• Strong incentives to limit them: save water in summer and users
requiring a better service • Towards automatic management
• Improve water resource management• Improve service to user• Facilitate irrigation canal operational management
Objective
• Canal dynamics are complex • Represented by nonlinear PDE: Saint-Venant equations• Linear approach leads to effective results• But no existing classification for canal dynamics
• Objective: understand the dynamics of linearized Saint-Venant equations
• Frequency domain approach• Poles• Spectral decomposition• From horizontal frictionless canal to uniform and non uniform
cases
Different views of irrigation canals
Outline
• Introduction• Modeling of open channel flow
• Spectral decomposition• Time domain response
• Illustrations• Horizontal frictionless case• Uniform flow case• Non uniform flow case
• Analysis of Preissmann discretization scheme• A link between Riemann invariants and frequency
domain approaches• Conclusion
Main irrigation canal
• Series of canal pools
• We consider a single pool of length L
Modeling of open-channel flow
• Saint-Venant equations• Mass conservation
• Momentum conservation
• Initial condition
• Boundary conditions
Friction slope:
Linearized Saint-Venant equations
• Linearized around (non uniform) steady flow
Frequency response
• Laplace transform leads to a distributed transfer matrix:
• Poles pk in the horizontal frictionless case
Spatial Bode plot (horizontal frictionless case)
Uniform flow case
• Poles
-3 -2 -1 0 1 2 3
x 10-3
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
real
imag
Spatial Bode plot (Uniform flow case)
Non uniform flow case
• Compute the distributed transfer function using an efficient numerical procedure (Litrico & Fromion, J. of Hydraulic Engineering 2004)
• Compute the poles using this numerical method• Conclusion: non uniform flow is qualitatively similar to
uniform flow
• Question: can we decompose the system along the poles?
• Answer: Yes!
Main result: spectral decomposition
• The elements gij(x,s) of the distributed transfer matrix G(x,s) can be decomposed as follows:
aij(k)(x) is the residue of gij(x,s) at the pole pk
Spatio-temporal representation of gij(x,s)
Sketch of proof
Define
gives
Apply the Cauchy residues theorem to on a series of nested contours CN
Implications
• SV transfer matrix belongs to the Callier-Desoer class of transfer functions
• Nyquist criterion provides a necessary and sufficient condition for input-output stability
• Link with exponential stability using dissipativity approach (see Litrico & Fromion, Automatica, 2009, in press)
Horizontal frictionless case
Residues aij(k)(x)
Residues aij(k)(x)
0 500 1000 1500 2000 2500 30000
0.5
1
1.5
2
2.5
3x 10
-5
abscissa (m)
|a11(k)(x)|
k=0
k=1k=2
k=3
Coeff aij(k)(x), Non uniform case, canal 1
0 500 1000 1500 2000 2500 30001.8
2
2.2
2.4
2.6
2.8
3
3.2
3.4x 10
-5 k=0
0 500 1000 1500 2000 2500 30000
0.5
1
1.5
2
2.5
3x 10
-5 k=1
0 500 1000 1500 2000 2500 30000
0.5
1
1.5
2
2.5
3x 10
-5
abscissa (m)
k=2
0 500 1000 1500 2000 2500 30000
0.5
1
1.5
2
2.5
3x 10
-5 k=3
abscissa (m)
-2.5 -2 -1.5 -1 -0.5 0
x 10-3
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
real
imag
acceleratinguniformdecelerating
0 500 1000 1500 2000 2500 30000
0.5
1
1.5
2
2.5
3canal 1
abscissa (m)
elev
atio
n (m
)
acceleratinguniformdecelerating
Bode plot: approximations with different numbers of poles
10-4
10-3
10-2
10-1
-45
-40
-35
-30
-25
-20
-15
-10
-5G
ain
(dB
)
p21
10-4
10-3
10-2
10-1
-100
-80
-60
-40
-20
0
20
Freq. (rad/s)
Pha
se (
deg)
10-4
10-3
10-2
10-1
-45
-40
-35
-30
-25
-20
-15
-10
-5
Gai
n (d
B)
p22
10-4
10-3
10-2
10-1
0
50
100
150
200
250
300
Freq. (rad/s)
Pha
se (
deg)
Time response
• Rational approximations
• Unit step response
Step response (horizontal frictionless case)
0 500 1000 1500 2000 2500 3000-0.02
0
0.02
0.04
0.06
0.08
time (s)
y11
0 500 1000 1500 2000 2500 30000
0.02
0.04
0.06
0.08
0.1
time (s)
y21
0 500 1000 1500 2000 2500 3000-0.1
-0.08
-0.06
-0.04
-0.02
0
time (s)
y12
0 500 1000 1500 2000 2500 3000-0.08
-0.07
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
time (s)
y22
Step response (uniform flow)
0 500 1000 1500 2000 2500 3000-0.02
0
0.02
0.04
0.06
0.08
time (s)
p11
0 500 1000 1500 2000 2500 30000
0.02
0.04
0.06
0.08
0.1
time (s)
p21
0 500 1000 1500 2000 2500 3000-0.05
-0.04
-0.03
-0.02
-0.01
0
time (s)
p12
0 500 1000 1500 2000 2500 3000-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
time (s)
p22
Spatial Bode plot (Uniform flow case, canal 2)
Coeff aij(k)(x), Non uniform case, canal 2
0 1000 2000 3000 4000 5000 60000
1
2
3
4
5
6
7
8canal 2
abscissa (m)
elev
atio
n (m
)
acceleratinguniformdecelerating
0 1000 2000 3000 4000 5000 60000
1
2
x 10-4 k=0
0 1000 2000 3000 4000 5000 60000
1
2
3
4
5
6
7
8x 10
-4 k=1
0 1000 2000 3000 4000 5000 60000
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6x 10
-4
abscissa (m)
k=2
0 1000 2000 3000 4000 5000 60000
1
2
3
4
5
6
7
8x 10
-5 k=3
abscissa (m)
-7 -6 -5 -4 -3 -2 -1 0
x 10-3
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
real
imag
acceleratinguniformdecelerating
Applications
• Preissmann scheme = Classical numerical scheme used to solve the equations
• We study the scheme on the linearized equations• We relate the discretized poles to the continuous ones
• Poles location as a function of t , x and
• Root locus with a downstream controller
Preissmann scheme
Study of the discretized system
• The linearized SV equations discretized with this scheme give
Assuming , the condition for the existence of a non trivial solution is
with
Study of the discretized system (cont’d)
or with
And finally
This equation is formally identical to the one obtained in the continuous time case!!!
One may show that the poles can be computed in two steps:• first compute the continuous time poles obtained due to the spatial discretization• then compute the discrete time poles
Example: effect of spatial discretization
• Horizontal frictionless case
1 2 3 4 5 6 7 8 90
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
mode
ima
g
Effect of parameter theta
-0.03 -0.02 -0.01 0 0.01 0.02 0.03-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
real
ima
g
=0.1=0.5=0.9
Bode plot of discretized system
10-5
10-4
10-3
10-2
10-1
-50
-40
-20
0
20Bode plot canal 1
freq.(rad/s)
ga
in (
dB
)
10-5
10-4
10-3
10-2
10-1
-1500
-1000
-500
0
freq.(rad/s)
ph
ase
(d
g)
A link between frequency domain and Riemann invariants methods
• For horizontal frictionless canals, Riemann invariants and frequency domain methods lead to the same result:
• Open-channel flow can be represented by a delay system• How to extend this to the case of nonzero slope and
friction?• For nonzero slope and friction, Riemann coordinates
are no longer invariants!• But frequency domain methods enable to diagonalize
the system…
Riemann invariants (horizontal frictionless case)
SV equations
Diagonalize matrix A
Laplace transform
This is a delay system!
Uniform flow case (with slope and friction)
Laplace transform + diagonalize matrix A-1(sI+B):
SV equations
New variables:
Uniform flow case (cont’d)
Solution in the Laplace domain:
« generalized » delay system
We have:
with
and
Solution in the time domain
Time evolution of generalized characteristics
with
Change of variables
Solution in the time domain (cont’d)
Change of variables
Inverse Laplace transform
Solution in the time domain
Inverse transform (time)
Application: motion planning
We want to find the controls steering the system from 0 to a desired state in a given time Tr. The evolution equation leads to:
Feedback control
Controller
or
with
System
Closed-loop system
Sufficient stability condition
Control of SV oscillating modes: root locus
Control of SV oscillating modes
Conclusion
• Analysis of linearized Saint-Venant equations • Poles and spectral decomposition
• Analytical results in horizontal frictionless and uniform cases• Numerical method in non uniform cases
• Rational models • Complete characterization of the flow dynamics• Analysis of Preissmann discretization scheme• Generalized characteristics (using Bessel functions)
• More details and applications in the book « Modeling and control of hydrosystems », Springer, to appear in 2009.