280 likes | 289 Views
This research explores the effectiveness of nonlinear observer designs for anti-slug control in multiphase systems. Various observer strategies are examined, including Unscented Kalman Filter and High-Gain Observer, to tackle challenges like nonlinear dynamics and unstable zero dynamics. Experimental results highlight the limitations and benefits of different observer approaches in stabilizing control in pressure-based systems.
E N D
Anti-Slug Control Experiments Using Nonlinear Observers Esmaeil Jahanshahi, Sigurd Skogestad, Esten I. Grøtli Norwegian University of Science & Technology (NTNU) American Control Conference - June 17th 2013, Washington, DC
Outline • Introduction • Motivation • Modeling • Observer design • Unscented Kalman Filter (UKF) • High-Gain observe • Fast UKF • State-feedback • Experimental results • Controllability limitation
Introduction * figure from Statoil
Slug cycle (stable limit cycle) Experiments performed by the Multiphase Laboratory, NTNU
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
Pt,s PC uz PT Motivation Objective: using topside pressure for control Problem 1: Nonlinearity Additional Problem 2: Unstable zero dynamics (RHP-zero) MS=5.87, MT=6.46
Nonlinear observer K State variables PT Solution?! uc uc Pt Questions: • Is this solution applicable for anti-slug control? • Can observer bypass fundamental limitations? • Which kind of observer is suitable? • Experiments
Modeling: Simplified 4-state model Choke valve with opening Z x3, P2,VG2, ρG2 , HLT P0 wmix,out L3 x1, P1,VG1, ρG1, HL1 x4 L2 h>hc wG,lp=0 wL,in wG,in w x2 wL,lp h L1 hc θ State equations (mass conservations law):
Experiments 3m
Bifurcation diagrams Experiment Top pressure Subsea pressure Gain = slope
1. Unscented Kalman Filter Nonlinear plant: (1) Prediction step:
1. Unscented Kalman Filter (UKF) (2) Update step: (3) Correction step:
2. High-Gain Observer where
3. Fast UKF Nonlinear model with transformed states: This is the high-gain observer without the observer term, therefore we do not need to specify the observer gain manually. High-gain Strategy: • Large Qk and small Rk increase the UKF gain • UKF gain: • - Scalingofstates and measurement in themodel
State Feedback Kc : a linear optimal controller calculated by solving Riccati equation Ki : a small integral gain (e.g. Ki = 10−3)
Experiment High-gain observer – top pressure measurement: topside pressurevalve opening: 20 %
Experiment Fast UKF – top pressure measurement: topside pressurevalve opening: 20 %
Experiment High-gain observer – subsea pressure measurement: topside pressurevalve opening: 20 %
Experiment PI Controller – subsea pressure measurement: subsea pressurevalve opening: 40 %
Experiment Linear observer (KF) – subsea pressure measurement: subsea pressurevalve opening: 40 %
Experiment Summary of experiments Stabilizing Control * Estimation works (open-loop), but slow * Estimation also not working
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
Controllability limitation – top pressure Measuring topside pressure we can stabilize the system only in a limited range RHP-zero dynamics of top pressure
Conclusions • Nonlinear observers work only when measuring topside pressure • This works in a limited range (valve opening) • A fast observer is needed for stabilizing control • Fast nonlinear observers fail when measuring subsea pressure • Observer can counteract nonlinearity • But cannot bypass fundamental limitation (non-minimum-phase system) Thank you!