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1 The thematic content of the series:
1 Facts Revenue from the last two years; Localization; History and surroundings 2 Research Six strategic areas; Three Centres of Excellence; Laboratories; Cooperation with SINTEF; 3 Education and student activities Study areas and programmes of study; Quality Reform; Further- and continuing education; Internationalization 4 Innovation and relationships with business and industry Innovative activities; Agreements with the public and private sectors 5 Dissemination Publications, events and the mass media Museum of Natural History and Archaeology, NTNU Library 6 Organization and strategy Board and organization; Vision, goal and strategies; For more on terminology, see (“terminologiliste”) See also (”Selected administrative terms with translations”) Nonlinear model-based control of two-phase flow in risers by feedback linearization Esmaeil Jahanshahi, Sigurd Skogestad, Esten I. Grøtli Norwegian University of Science & Technology (NTNU) 9th IFAC Symposium on Nonlinear Control Systems – September 4th 2013, Toulouse

2 Outline Introduction Motivation Modeling
Solution 1: State estimation & state feedback Solution 2: Output linearization Experimental results Controllability limitation

3 Introduction * figure from Statoil

4 Slug cycle (stable limit cycle)
Experiments performed by the Multiphase Laboratory, NTNU

5 Introduction Anti-slug solutions Conventional Solutions:
Choking (reduces the production) Design change (costly) : Full separation, Slug catcher Automatic control: The aim is non-oscillatory flow regime together with the maximum possible choke opening to have the maximum production

6 Motivation Problem 1: Nonlinearity
PT PC uz Pt,s Problem 1: Nonlinearity Additional Problem 2: Unstable zero dynamics (RHP-zero) for topside pressure

7 Modeling

8 Modeling: Simplified 4-state model
θ h L2 hc wmix,out x1, P1,VG1, ρG1, HL1 x3, P2,VG2, ρG2 , HLT P0 Choke valve with opening Z x4 h>hc wG,lp=0 wL,lp L3 wL,in wG,in w x2 L1 State equations (mass conservations law):

9 Experiments 3m

10 Bifurcation diagrams Top pressure Subsea pressure Gain = slope
Experiment Bifurcation diagrams Top pressure Subsea pressure Gain = slope

11 Solution 1: observer & state feedback
PT Nonlinear observer K State variables uc Pt

12 High-Gain Observer

13 State Feedback Kc : a linear optimal controller calculated by solving Riccati equation Ki : a small integral gain (e.g. Ki = 10−3)

14 High-gain observer – top pressure
Experiment High-gain observer – top pressure measurement: topside pressure valve opening: 20 %

15 Fundamental limitation – top pressure
Measuring topside pressure we can stabilize the system only in a limited range RHP-zero dynamics of top pressure Z = 20% Z = 40% Ms,min 2.1 7.0

16 High-gain observer – subsea pressure
Experiment High-gain observer – subsea pressure measurement: topside pressure valve opening: 20 % Not working ??!

17 Chain of Integrators Fast nonlinear observer using subsea pressure: Not Working??! Fast nonlinear observer (High-gain) acts like a differentiator Pipeline-riser system is a chain of integrator Measuring top pressure and estimating subsea pressure is differentiating Measuring subsea pressure and estimating top pressure is integrating

18 Solution 2: feedback linearization
PT Nonlinear controller uc Prt

19 Cascaded system

20 Pipeline subsystem ISS
Hypothesis 1. The Pipeline subsystem with the riser-base pressure, Prb, as its input is “input-to-state stable”.

21 Stability of cascade system
Riser Proposition 2. Let hypothesis 1 holds. If the Riser subsystem becomes globally asymptotically stable under a stabilizing feedback control, then the pipeline-riser system is globally asymptotically stable. Proof : We use conditions for stability of the cascaded systems as stated by Corollary of Isidori (1999).

22 Stabilizing controller for riser subsys.
Riser dynamics: System equations in y coordinates:

23 Stabilizing controller for riser subsys.
exist and are continuously differentiable. is a diffeomorphism on

24 Stabilizing controller for riser subsys.
System in normal form: Feedback controller: (1) Reduces to . By choosing , we get exponentially stable

25 Stabilizing controller for riser subsys.
If we insert the control law into (2) we get Since , K1 is bounded and exponentially fast, will remain bounded. This is partial exponential stabilization of the system with respects to . (Vorotnikov (1997))

26 Stabilizing controller for riser subsys.
Final control law by linearizing y1 dynamics, equation (1): In the same way by linearizing y2 dynamics, equation (2): y2 is non-minimum phase Control signal to valve:

27 CV: riser-base pressure (y1), Z=30%
Experiment CV: riser-base pressure (y1), Z=30%

28 CV: riser-base pressure (y1), Z=60%
Experiment CV: riser-base pressure (y1), Z=60% Gain:

29 CV: topside pressure (y2), Z=20%
Experiment CV: topside pressure (y2), Z=20% y2 is non-minimum phase

30 Conclusions Nonlinear observers work only when measuring topside pressure This works in a limited range (valve opening of 20%) Nonlinear observers fail when measuring subsea pressure New controller (without observer) stabilizes system up to 60% World record (on our experiment)! Tie with gain-scheduled IMC But cannot bypass fundamental limitations: non-minimum-phase system for topside pressure Small gain of system for large valve openings Thank you!


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