Titolo presentazione
sottotitolo
Dynamics and Control of Chemical Processes
Matteo Pelucchi
Milano, XX mese 20XX
Contacts
Email: matteo.pelucchi@polimi.it
Phone: +39 02 2399 4234
Dynamics and Control of Chemical Processes: Lecture #0
Introduction: myself in brief
Education:
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•
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Bachelor in Chemical Engineering, 2010, POLIMI (Supervisor: T. Faravelli, A. Cuoci)
Master in Chemical Engineering, 2013, POLIMI (Supervisor: E. Ranzi, T. Faravelli, H.J.
Curran)
PhD in Industrial Chemistry and Chemical Engineering, 2017, POLIMI (Supervisor: T.
Faravelli)
Visiting positions:
•
•
Visiting master student at the Combustion Chemistry Centre, School of Chemistry,
National University of Ireland, Galway, 2012 (H.J. Curran)
Visiting graduate student at the Chemical Science and Engineering Division, Argonne
National Laboratory, Argonne, IL, USA, 2016 (S.J. Klippenstein)
Current position:
•
•
Tenure Track Assistant Professor (RTDb) of Chemical Engineering
SSD: «Theory and Development of Chemical Processes» (ING-IND/26)
Other institutional duties:
•
•
•
Secretary, Study Program (CCS) in Chem. Eng. and IPSIP (s. 2023)
Head of Communication and Promotion, Study program in Chem. Eng. (2019-2022)
Permanent Committee (CPCCS) member, Study Program in Chem. Eng and IPSIP (s. 2021)
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Introduction: myself in brief
Previous and current teaching activities:
•
Combustion fundamentals, teaching assistant, 2014-2020
•
Combustion and pollutant formation, teaching assistant, 2015-2016
•
Sperimentazione Industriale, teaching assistant, 2017-2018
•
Dynamics and Control of Chemical processes, 5CFU, Lecturer, 2019-present
•
3.5
Laboratorio Progettuale di Ing. Chimica, 8CFU, Lecturer,
2021-present
Global student evaluation index
DCOCP
POLIMI
Research interests (CRECK Modeling Lab, creckmodeling.chem.polimi.it):
3.3
3.4
•
Kinetic models of complex reaction systems
•
Energy
•
Combustion, pollution, fuels development (bio, biomass,
conventional)
2.9
•
2.8
Theoretical kinetics (ab initio transition state theory,
molecular
dynamics)
2019
2020
2021
•
Databases, data analysis and management, model analysis
•
Circular economy processes (pyrolysis, gasification): chemical recycling of plastic waste,
hydrogen and carbon materials production
•
…more info to come, if you are interested in MSc thesis projects @CRECK
3.2
3.1
3
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
2022
3
CRECK Modeling Lab
PhD Students
Staff
Tiziano
Faravelli
Alessio
Frassoldati
Andrea Locaspi
Alessandro
Pegurri
Alberto
Cuoci
Marco
Mehl
Andrea Nobili
Timoteo Dinelli
Alessandro
Stagni
Matteo
Pelucchi
Francesco Serse
Clarissa Giudici
Luna
Pratali Maffei
Isabella Branca
Administration
Edoardo Cipriano
Edoardo Ramalli
(DEIB)
Romina Papagni
Ahsan Amjed
(DENG)
http://creckmodeling.chem.polimi.it/
4
Andrea Schirru
(DENG)
+2 Visiting PhD, +10 Master Students
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
CRECK Modeling Lab
http://creckmodeling.chem.polimi.it
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
CRECK Modeling Lab
Multiscale approach to reactive flows modeling
CFD modeling of industrial
scale reactors
(gasifiers, FB, surface
reactors, burners, engines)
chemistry/turbulence
interactions modelling
Chemistry, heat
and mass transfer
Chemistry model
validation
Development
Industrial
applications
Non-premixed lab-scale turbulent reactive
flows (MILD combustion, burners, catalytic
reactors)
1D-2D reactors modelling, Numerical methods development
Ideal 0D-1D reactors (batch, PSR, PF), drop tubes, thermo-gravimetric
analysis, surface reactors
Determination of accurate chemical kinetics, thermodynamics and transport properties
from fundamental theories
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
Introduction: course structure
Lectures/Practicals/Seminars:
•
Wednesday
15.30-17.00
T.0.4
•
Thursday
10.30-12.00
T.0.2
17 Lectures + 9 Computational Laboratories + 2 industry seminars
•
Computational Laboratories by Ing. Clarissa Giudici clarissa.giudici@polimi.it
•
Lecture Material: 75% on blackboard (no additional material provided) + 25%
powerpoint slides (provided in advance on WeBeep)
Structure of the course:
•
Part1: Modeling and analysis of the dynamic behavior of chemical processes
•
Part2: Analysis and design of feedback controllers
•
Part3: Advanced control systems
•
Part4: Introduction to plant control
•
Part5: System Identification and Model Predictive Control
Course is largely (~70%) based on
«Chemical Process Control: An Introduction to Theory and Practice» By G. Stephanopoulos, MIT, USA
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Introduction: course structure and exams
Practicals:
• 9 Sessions
• 1 pen on paper + 7 Matlab + 2 Unisim process simulator, (access to remote
desktop will be provided to each one of you, so you can «play» with Unisim
at home!)
• Note: we will not always proceed alternating lectures and practicals as some
topic might require 2/3 lectures in a row to be properly addressed. Keep an
eye on the calendar!
Exams:
• Oral interview only + Report on ALL practicals (1 or 2 students)
• Booking via email required in advance
• Report on practicals mandatory (all practicals) to be submitted in advance
(4/5 days before the exam date). Some kind of creativity is very much
appreciated. (Mark: -1 to 2 points over 30)
• No official registration = No exam
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Introduction: course structure and exams
Exam dates:
• Official dates (∼6/7 students max)
• Thursday 15th June, 9.30-12.30 + 14.00-17.00
• Thursday 20th July, 9.30-12.30 + 14.00-17.00
• + Other non-official dates (during exam session)
∼ Every Thursday morning (9.30-12.30, ∼3/4 students max)
• 08/06/23
• 22/06/23 (TBC)
• 29/06/23
• 06/07/23
• 27/07/23
• 31/08/23
• 14/09/23
• 21/09/23
I will keep you updated on possible date changes
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Calendar (tentative): Part 1
Modeling and analysis of the dynamic behavior of chemical processes
Wednesday 22nd February
L1
Design aspects, elements, types of control configuration,
Introduction and exams, Introduction to chemical process control general features of a control system, hardware for process
control
Thursday 23rd February
L2
Modelling the dynamic and static behavior of chemical processes
(1)
Wednesday 1st March
L3
Modelling the dynamic and static behavior of chemical processes
(2)
Thursday 2nd March
L4
Analysis of the dynamic behavior of chemical processes (1)
Input/Output models, degrees of freedom
Wednesday 8th March
L5
Analysis of the dynamic behavior of chemical processes (2)
linearization of non linear systems, Laplace transforms
and application examples
Thursday 9th March
L6
Analysis of the dynamic behavior of chemical processes (3)
Transfer functions and the Input/Ouput model.
Wednesday 15th March
P1
Introduction to system dynamics using Matlab
Batch reactor, heated tank, mixing process, CSTR
Thursday 16th March
P2
Laplace transform
Solution of chemical engineering problems with Laplace,
Application examples of Laplace transform,
Wednesday 22nd March
L7
Analysis of the dynamic behavior of chemical processes (4)
Dynamics of first and second order systems
Mathematical model, state variables and equations,
examples (tank heater, +flash tank)
Recap + Examples: CSTR, mixing tank, binary distillation
column.
Starts at 3 pm
Starts at 3 pm
Subject to change depending on how fast we can proceed:
STOP ME AT ANY TIME if I’m too fast and ASK QUESTIONS!
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Calendar (tentative): Part 2
Analysis and Design of Feedback controllers
Date
Topic
Details
Thursday 23rd March
P3
System dynamics using Matlab
Dynamics of a tank and two interacting or non-interacting
tanks
Wednesday 29th March
L8
Analysis and design of feedback control systems (1)
Recap, controller effects on systems dynamics,
Introduction to FB control
Thursday 30th March
L9
Analysis and design of feedback control systems (2)
FB controller effects on first and second order systems
dynamics, stability analysis
Wednesday 5th April
L10
Analysis and design of feedback control systems (3)
Stability analysis, Design of FB controllers
Thursday 6th April
P4
Feedback control design Using Matlab (1)
Cohen and Coon
Wednesday 12th April
P5
Feedback control design Using Matlab (2)
ISE, IAE, ITAE
Thursday 13th April
L11
Analysis and design of feedback control systems (4)
Frequency response analysis of linear processes, Bode
diagrams
No lectures on 19th, 20th April, 4th May
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Calendar (tentative): Part 3
Advanced Control Systems
Date
Topic
Details
Wednesday 26th April
L12
Advanced control systems (1)
Systems with large dead times, cascade and selective
control
Thursday 27th April
L13
Advanced control systems (2)
Feedforward and ratio control
Wednesday 3rd May
L14
Advanced control systems (3) + Plant Control (0)
Adaptive and inferential control, Introduction to plant
control, MIMO systems
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Calendar (tentative): Part 4
Plant Control
Date
Topic
Details
Wednesday 10th May
L15
Plant Control (1)
Interaction and decoupling of control loops
Thursday 11th May
P6
Unisim Process Simulator
Examples: flash tank, absorption column, plug flow reactor
Wednesday 17th May
L16
Plant Control (2)
Design of control systems for complete plants, process and
distillation column examples
Thursday 18th May
P7
Unisim Process Simulator
Dynamics and control (same examples + column)
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Calendar (tentative): Part 5
System Identification, Model Predictive Control, Seminars
Date
Topic
Details
Wednesday 24th May
L17
System Identification (1) + Model Predictive Control
Recap on plant control, Process identification (black box
models from experimental data), Introduction to model
predictive control
Thursday 25th May
P8
Matlab toolbox
Black Box Models
Wednesday 31st May
P9
MPC
Examples (matlab toolbox)
Thursday 1st June
S
Seminars from Industry Speakers
DOW, Alpha Process Control
Seminars (Thursday 01/06/23)
1. Ing. Flavia Cannavale – DOW, Parona
2. Ing. Cosimo Antonio Carnuccio – Alpha Process Control, Pisa
Attendance to seminars is mandatory.
No seminars = No Exam
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Recordings and streaming
Lecture and practicals will be recorded (no streaming).
Recordings will be provided only to students that certify one of the following:
1. Overlapping classes (please provide your study plan and timetables)
2. Impossibility to participate (due to illness, delays in transfers from home
institutions, transport strikes)
3. Other issues for which I will be automatically notified (e.g. multichance,
double careers, etc.)
Recordings may be removed after 2 weeks
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Objectives
1. Understanding how to analyze the dynamic behavior of a process subject
to:
• Undesired events (disturbances)
• Intentional changes (set point change)
2. Developing dynamic models to simulate the behavior of more or less simple
systems using conservation equations
3. Understanding how the equipment design parameters and the process
operating parameters affect the dynamic response
4. Understanding how to design a process control sysytem and how to make it
effective
5.
• Variables to be controlled to ensure that the process is running
satisfactorily
• Variables to be manipulated and how to reject external disturbances
Get to know the concepts and trends in Model Predictive Control and
massive data usage (big data)
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Expected learning outcomes
In the case of successful completion of the exam,
the student knows:
• the conservation equations to model the dynamics of chemical processes and
how to implement them in numerical tools (e.g. using Matlab)
• the features and criticisms of a dynamic system
• the fundamentals of process control
• advantages and shortcomings of different control strategies and is able to
choose appropriate control techniques for specific cases
• How to design effective controllers
• How to tackle the dynamics of simple systems using commercial software
packages for process simulation and control
• How to critically discuss about process dynamics and process control with an
adequate technical language.
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Additional clarifications and comments
• No material (i.e. slides) provided for a large part of course lectures (75% is on
blackboard)! I told you!
• Yes…those that have graduated at Politecnico have seen already some of the
topics (e.g. feedback control (FBC) with Prof. Davide Manca, mass/energy
balances of simple units, etc. ). But…
• FBC is needed for you to understand more advanced strategies;
• Prof. Davide Manca’s course focuses strictly on «time domain», we will be
focusing on both «time domain» and «Laplace domain» which is at the
basis of process control logics and theories;
• Those that graduated from outside Politecnico most probably have not
seen anything about FBC so far;
• The course is available also for Automation Engineering students that have
no background on mass/energy balances for chemical plants units
• Help me regulate my speed
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Modeling Dynamic System
General concepts
• Most of the engineers construct models
• Model is a «more or less complicated» mathematical representations of a
system, useful to:
• Interpret measured data (experiments, plant data…)
• Make predictions of what will happen
• Design processes and control systems
• Processing signals
• A system is «a real thing»
• A dynamic system is «a system with memory»: how it reacts to an input
depends on its previous history (what happened before, what you have done
to it…)
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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What is a system? Is a real thing…
Inputs
•
•
•
•
•
•
Outputs
Thrust
…
Feedstock composition
Feedstock temperature
Ambient temperature
Target product specification
•
•
•
•
•
Speed
…
Purity of products
Hazardous emissions
Production capacity…
Output
Input
time
time
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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How do we get to know a system? Can we model it? How?
Inputs
Outputs
Model
Measuring device
How is the output related to the input?
How does the input impacts the output?
O=f(time, I, …)
Output
Input
time
time
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Modeling approaches
First-principles
Modeling
(white box)
Model
• If I know/can model the physics (fluid
dynamics, chemistry,
thermodynamics…) of the system
Data-driven
Modeling
(black box)
• Does not require the knowledge of a
system
• Based on conservation equations
• A model is constructed only based on
observed data from a dynamic system
• Requires the solution of a system of
equations (ODE)
• Is a more or less symple mathematical
expression (e.g. polynomials)
• Requires a validation with experiments
(how good is my model?)
• Is valid in the validation range by
definition as it is fitted on data
• Being based on first principles should
be reliable outside validation ranges
• Is strictly valid only within the
validation range
Matteo Pelucchi, DCoCP – Introduction, Lecture #0
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Dynamics and Control of Chemical Processes
• If I don’t know a system, I can’t control it.
 We will develop models for typical chemical engineering applications in
the time domain (conservation equations)
• Chemical engineering processes are very often non-linear
 We will learn how to linearize models and to solve them in the Laplace
domain
• Once I know the system how can I control it?
 We will learn how to conceive and design suitable control strategies
 We will learn the best practices
• How does the system react to disturbances or to manipulated inputs?
 We will learn what are typical process responses to variable inputs
• What are the advantages and disadvantages of white box and black box?
 We will cover first-principles modeling (85%) and data-driven modeling
(15%)
• Engineering, technology and science are proceeding fast…
 We will learn recent trends and understand future perspectives
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