1 Christer Haugland, Modeling and Control of fertilizer granulation process Christer Haugland Supervisors: Sigurd Skogestad Vidar Alstad (Yara Technology.

Slides:



Advertisements
Similar presentations
Tuning of PID controllers
Advertisements

I. Energy Flow A. Producers Make their own food through photosynthesis
Properties of Matter 2.1 Matter has observable properties. 2.2
CIMExcel Software Inc. Slide 1 Performance Solutions for the Mineral Processing Industry for Pit to Plant Optimization Optimal Mineral Processing Control.
Optimization of parameters in PID controllers Ingrid Didriksen Supervisors: Heinz Preisig and Erik Gran (Kongsberg) Co-supervisor: Chriss Grimholt.
Specialization project 2012 Temperature control of an unstable chemical reactor By Ola Sæterli Hjetland Supervisors: Sigurd Skogestad, Krister Forsman.
RECRYSTALLIZATION.
What gas velocities are required? For particles larger than 100  m –Wen&Yu correlation Re mf =33.7[(1+3.59*10 -5 Ar) ] –Valid for spheres in the.
Chemistry. Describing Matter  Matter – anything that has a mass and takes up space. Air, plastic, metal wood, glass, paper, and water are all matter.
Changes in Matter Chapter 2 Section 3.
Properties, Handling and Mixing of Particulate Solids
Plantwide process control with focus on selecting economic controlled variables («self- optimizing control») Sigurd Skogestad, NTNU 2014.
Practical plantwide process control Sigurd Skogestad, NTNU Thailand, April 2014.
PID Tuning and Controllability Sigurd Skogestad NTNU, Trondheim, Norway.
Name: Period: Science 6th Grade
Wittaya Julklang, Boris Golman School of Chemical Engineering Suranaree University of Technology STUDY OF HEAT AND MASS TRANSFER DURING FALLING RATE PERIOD.
Control of floor heating process Siri Hofstad Trapnes Supervisors: Sigurd Skogestad and Chriss Grimholt Direct heating in the floor and room Keep the temperature.
GHGT-8 Self-Optimizing and Control Structure Design for a CO 2 Capturing Plant Mehdi Panahi, Mehdi Karimi, Sigurd Skogestad, Magne Hillestad, Hallvard.
PRODUCTION OF UREA. Urea is a white dry organic compound and a crystalline substance and has minimum of 46% Nitrogen calculated in dry state. M.P: 132.
1 Modelling, Operation and Control of an LNG Plant Jens Strandberg & Sigurd Skogestad Department of Chemical Engineering, Norwegian University of Science.
RELATIVE GAIN MEASURE OF INTERACTION We have seen that interaction is important. It affects whether feedback control is possible, and if possible, its.
SAURAV SHARMA 2013UGMM001 ITESH KUMAR TAMSOY 2013UGMM002 NISHANT KUMAR 2013UGMM017.
PSE and PROCESS CONTROL
Department of Chemical Engineering,
ATOMIC STRUCTURE Notes are for your personal use. Abbreviate as you see fit.
Simple rules for PID tuning Sigurd Skogestad NTNU, Trondheim, Norway.
What the Matter? Chem Review. Questions for Today What are the common elements used in Environmental Science? What is an Ion and what are the common ions.
8. Hydro- sphere 7. Atmosphere 5. Forests and semi- natural ve- getation 3. Humans and settle- ments 4. Agriculture 2. Materials +products in industry.
1 E. S. Hori, Maximum Gain Rule Maximum Gain Rule for Selecting Controlled Variables Eduardo Shigueo Hori, Sigurd Skogestad Norwegian University of Science.
Food Chains & Food Webs. Food chain  Food chain: A model that shows how energy and matter move through an ecosystem AcornSquirrelRed-tailed hawk AcornSquirrelRed-tailed.
The mined ore rocks are very large and have to be made smaller. This is done by a machine called a jaw crusher. The resulting smaller rocks are further.
1 Outline Control structure design (plantwide control) A procedure for control structure design I Top Down Step 1: Degrees of freedom Step 2: Operational.
 Anything that has mass and takes up space  Made up of tiny particles called atoms  Atoms: smallest particle of matter.
1 Decentralized control Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Tecnology (NTNU) Trondheim, Norway.
1 1 Vinicius de Oliveira | an intelligent adaptive anti-slug control system for production maximization Vinicius de Oliveira Control and Automation Engineering.
1 Modelling of Biodiesel Production Marianne Øien Supervisors: Sigurd Skogestad and Chriss Grimholt.
1 Unconstrained degrees of freedom: C. Optimal measurement combination (Alstad, 2002) Basis: Want optimal value of c independent of disturbances ) – 
MISS. RAHIMAH BINTI OTHMAN
SOLID,LIQUID,GAS BY: Sajedah Ghizawi 6E. Solid Solid Is one of the three classical states of matter, the others being gas and liquid. Solid Is one of.
1 Elements, Compounds, and Mixtures. 2 What is Matter?  Matter is anything that has mass and volume.  All matter is composed of tiny particles.  Arrangement.
Control strategies for optimal operation of complete plants Plantwide control - With focus on selecting economic controlled variables Sigurd Skogestad,
Pure Substances.
Coordinator MPC with focus on maximizing throughput
Particle Size Reduction Machines
How does the Mass of a Penny Change with Age?
Sigurd Skogestads 60th celebration day
Probably© the smoothest PID tuning rules in the world: Lower limit on controller gain for acceptable disturbance rejection Sigurd Skogestad Department.
The Atomic Theory The smallest particle of an element that can enter into chemical change. 2. Building block of all matter. 3. Consists of a central nucleus.
Advanced process control with focus on selecting economic controlled variables («self-optimizing control») Sigurd Skogestad, NTNU 2016.
Ert 318 : unit operations operations involving particulate solids
Introduction to PID control
ELEMENTS, COMPOUNDS, AND REACTIONS UNIT 3
MECHANICAL OPERATION IN CHEMICAL ENGINEERING
Changing between Active Constraint Regions for Optimal Operation: Classical Advanced Control versus Model Predictive Control Adriana Reyes-Lúa, Cristina.
Formation of a new substance vocabulary
Classifying Matter: Atoms, Elements, & Molecules
Changes of State d. Students know the states of matter (solid, liquid, gas) depend on molecular motion. e. Students know that in solids the atoms are closely.
Outline Skogestad procedure for control structure design I Top Down
Controllability of a Granulation Process
EOG Review Notes Chemistry 8.P.1.
8.3 Phases of Matter On Earth, pure substances are usually found as solids, liquids, or gases. These are called phases of matter.
Operation and Control of Divided Wall (Petlyuk) Column
Physical Science Chapter 16
States of Matter Changes What’s the Matter? You BETTER Know This! More
Formation of a New Substance
Unit 1 – Atomic Structure
Energy Chapter 12 Section 1
Performance and Robustness of the Smith Predictor Controller
PID control of unstable chemical reactor
Matter and Change Unit 1.
Presentation transcript:

1 Christer Haugland, Modeling and Control of fertilizer granulation process Christer Haugland Supervisors: Sigurd Skogestad Vidar Alstad (Yara Technology Center) Modeling and Control of Fertilizer Granulation Process

2 Outline Fertilizer and granulation Process description Modeling –New crusher model Control –Re-tuned recycle mass flow controller –Added particle size controller

3 Fertilizer A major product in the world’s chemical industry Keep up with the increasing food demand in the world One important process step in making fertilizer is granulation.

4 Granulation Granulation consist of solidifying fertilizer melt into small granules which can be used in the agriculture. Solid granule particles are about 3 mm in diameter.

5 Process description Feed: Slurry melt Atomizing air Spherodizer: Drying Granulation Screen Separation based on size Crusher Crush oversize particles

6 Spherodizer

7 Recycle mass flow controller Split range controller

8 Modeling Old crusher model New crusher model Based on work done by Yara in MATLAB Extended with new crusher model

9 Control Re-tuning of recycle mass flow controller Based on open loop step response in model

10 Re-tuning of recycle mass flow controller Two model approximations: First order plus delay: Pure delay:

11 Re-tuning of recycle mass flow controller Gain variations in split range controller valves. k 2 = -670 k 1 = -295

12 Process gain variations in MV’s: –Gain scheduling control (one controller for each MV) –Changing the split in the split range controller (usually set at 50%) Gain scheduling: Re-tuning of recycle mass flow controller

13 Comparing the two with a ”trial and error” approach: Re-tuning of recycle mass flow controller

14 Re-tuning of recycle mass flow controller First order plus delay model: Not a good approximation! SIMC rules:

15 Re-tuning of recycle mass flow controller Comparing the two model approximations: Pure delay best!

16 Particle size control Added another PI controller to control particle sizes in granulator loop. Vibration in screen as MV, D50 out of granulator as CV. –But the MV saturated!!

17 Particle size control Recycle mass flow controller

18 Thank you!