A method for distributed control of nonlinear flow equations is proposed. In this method, first, Takagi–Sugeno (T–S) fuzzy model is used to substitute the nonlinear partial differential equations (PDEs) governing the system by a set of linear PDEs, such that their fuzzy composition exactly recovers the original nonlinear equations. This is done to alleviate the mode-interaction phenomenon occurring in spectral treatment of nonlinear equations. Then, each of the so-obtained linear equations is converted to a set of ordinary differential equations (ODEs) using the fast Fourier transform (FFT) technique. Thus, the combination of T–S method and FFT technique leads to a number of ODEs for each grid point. For the stabilization of the dynamics of each grid point, the use is made of the parallel distributed compensation (PDC) method. The stability of the proposed control method is proved using the second Lyapunov theorem for fuzzy systems. In order to solve the nonlinear flow equation, a combination of FFT and Runge–Kutta methodologies is implemented. Simulation studies show the performance of the proposed method, for example, the smaller settling time and overshoot and also its relatively robustness with respect to the measurement noises.

References

1.
Hashemi
,
S. M.
, and
Werner
,
H.
,
2012
, “
Gain-Scheduled Controller Synthesis for a Nonlinear PDE
,”
Int. J. Control
,
85
(
1
), pp.
88
97
.
2.
Baker
,
J.
,
Armaou
,
A.
, and
Christofides
,
P. D.
,
2000
, “
Nonlinear Control of Incompressible Fluid Flow: Application to Burgers Equation and 2D Channel Flow
,”
J. Math. Anal. Appl.
,
252
(
1
), pp.
230
255
.
3.
Park
,
H. M.
, and
Jang
,
Y. D.
,
2003
, “
Control of Burgers Equation by Means of Mode Reduction
,”
Int. J. Eng. Sci.
,
38
(
7
), pp.
275
805
.
4.
Smaoui
,
N.
,
2005
, “
Boundary and Distributed Control of the Viscous Burgers Equation
,”
J. Comput. Appl. Math.
,
182
(
1
), pp.
91
104
.
5.
Kunisch
,
K.
, and
Volkwein
,
S.
,
1999
, “
Control of the Burgers Equation by a Reduced-Order Approach Using Proper Orthogonal Decomposition
,”
J. Optim. Theory Appl.
,
102
(
2
), pp.
345
371
.
6.
Hinze
,
M.
, and
Volkwein
,
S.
,
2002
, “
Analysis of Instantaneous Control for the Burgers Equation
,”
Nonlinear Anal.
,
50
(
1
), pp.
1
26
.
7.
Kunisch
,
K.
, and
Xie
,
L.
,
2005
, “
POD-Based Feedback Control of the Burgers Equation by Solving the Evolutionary HJB Equation
,”
Comput. Math. Appl.
,
49
(7–8), pp.
1113
1126
.
8.
King
,
B. B.
, and
Krueger
,
D. A.
,
2003
, “
Burgers' Equation: Galerkin Least-Squares Approximations and Feedback Control
,”
Math. Comput. Modell.
,
38
(
10
), pp.
1075
1085
.
9.
Volkwein
,
S.
,
2001
, “
Distributed Control Problems for the Burgers Equation
,”
Comput. Optim. Appl.
,
18
(
2
), pp.
115
140
.
10.
Efe
,
M. O.
,
2005
, “
Fuzzy Boundary Control of 2D Burgers Equation With an Observer
,”
IEEE Conference on Control Applications
(
CCA
), Toronto, ON, Aug. 28–31, pp.
73
77
.
11.
Gorner
,
S.
, and
Benner
,
P.
,
2006
, “
MPC for the Burgers Equation Based on an LQG Design
,”
Proc. Appl. Math. Mech.
,
6
(
1
), pp.
781
782
.
12.
Krstic
,
M.
,
Magnis
,
L.
, and
Vazquez
,
R.
,
2008
, “
Nonlinear Stabilization of Shock-Like Unstable Equilibria in the Viscous Burgers PDE
,”
IEEE Trans. Autom. Control
,
53
(
7
), pp.
1678
1683
.
13.
Krstic
,
M.
,
Vazquez
,
R.
, and
Magnis
,
L.
,
2009
, “
Nonlinear Control of the Viscous Burgers Equation: Trajectory Generation, Tracking, and Observer Design
,”
ASME J. Dyn. Syst. Meas. Control
,
131
(
2
), p.
021012
.
14.
Thevenet
,
L.
,
Buchot
,
J.-M.
, and
Raymond
,
J.-P.
,
2010
, “
Nonlinear Feedback Stabilization of a Two-Dimensional Burgers Equation
,”
ESAIM: COCV
,
16
(
4
), pp.
929
955
.
15.
Buchot
,
J.-M.
,
Raymond
,
J.-P.
, and
Tiago
,
J.
,
2015
, “
Coupling Estimation and Control for a Two Dimensional Burgers Type Equation
,”
ESAIM: COCV
,
21
(
2
), pp.
535
560
.
16.
Chowdhury
,
S.
,
Maity
,
D.
,
Ramaswamy
,
M.
, and
Raymond
,
J.-P.
,
2015
, “
Local Stabilization of the Compressible Navier–Stokes System, Around Null Velocity, in One Dimension
,”
J. Differ. Equations
,
259
(
1
), pp.
371
407
.
17.
Vasegh
,
N.
, and
Khellat
,
F.
,
2013
, “
Takagi–Sugeno Fuzzy Modeling and Chaos Control of Partial Differential Systems
,”
Chaos
,
23
(
4
), p.
042101
.
18.
Christofides
,
P. D.
, and
Armaou
,
A.
,
1998
, “
Nonlinear Control of Navier–Stokes Equations
,”
IEEE American Control Conference
(
ACC
), Philadelphia, PA, June 24–26, pp.
1355
1359
.
19.
Fursikov
,
A. V.
,
2001
, “
Stabilizability of Two-Dimensional Navier–Stokes Equations With Help of a Boundary Feedback Control
,”
J. Math. Fluid Mech.
,
3
(
3
), pp.
259
301
.
20.
Posta
,
M.
, and
Roubiseck
,
T.
,
2007
, “
Optimal Control of Navier–Stokes Equations by Oseen Approximation
,”
Comput. Math. Appl.
,
53
(3–4), pp.
569
581
.
21.
Coron
,
J. M.
, and
Guerrero
,
S.
,
2009
, “
Local Null Controllability of the Two-Dimensional Navier–Stokes System in the Torus With a Control Force Having a Vanishing Component
,”
J. Math. Pures Appl.
,
92
(
5
), pp.
528
545
.
22.
Burkardt
,
J.
,
Gunzburger
,
M.
, and
Lee
,
H.-C.
,
2006
, “
POD and CVT-Based Reduced-Order Modeling of Navier–Stokes Flows
,”
Comput. Methods Appl. Mech. Eng.
,
196
(1–3), pp.
337
355
.
23.
Monokrousos
,
A.
,
Brandt
,
L.
,
Schlatter
,
P.
, and
Henningson
,
D. S.
,
2008
, “
DNS and LES of Estimation and Control of Transition in Boundary Layers Subject to Free-Stream Turbulence
,”
Int. J. Heat Fluid Flow
,
29
(
3
), pp.
841
855
.
24.
Lasiecka
,
I.
, and
Triggiani
,
R.
,
2015
, “
Stabilization to an Equilibrium of the Navier–Stokes Equations With Tangential Action of Feedback Controllers
,”
Nonlinear Anal.: Theory, Methods Appl.
,
121
, pp.
424
446
.
25.
Takagi
,
T.
, and
Sugeno
,
M.
,
1985
, “
Fuzzy Identification of Systems and Its Applications to Modeling and Control
,”
IEEE Trans. Syst., Man, Cybern.
,
15
(1), pp.
116
132
.
26.
Tanaka
,
K.
, and
Wang
,
H.
,
2001
,
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
,
Wiley
, Hoboken, NJ.
27.
Moin
,
P.
,
2010
,
Fundamentals of Engineering Numerical Analysis
,
Cambridge University Press
,
Cambridge
.
28.
Seidi
,
M.
, and
Markazi
,
A. H. D.
,
2011
, “
Performance-Oriented Parallel Distributed Compensation
,”
J. Franklin Inst.
,
348
(
7
), pp.
1231
1244
.
29.
Cooley
,
J. W.
, and
Tukey
,
J. W.
,
1965
, “
An Algorithm for the Machine Calculation of Complex Fourier Series
,”
Math. Comput.
,
19
(
90
), pp.
297
301
.
30.
Trefethen
,
L. N.
,
2000
,
Spectral Methods in MATLAB
,
SIAM
, Philadelphia, PA.
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