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Process Control and Identification, Academic year 2023-2024
Module 2 (Francesco Liberati)
Next exams:
Extraordinary session: lun 18/3/24, Aula A3 DIAG, 14:00-17:00.
8-gen, B2 DIAG, ORE 14-19.
8-feb, B2 DIAG, ORE 14-19.
mer 5/6/24, Aula 13 SPV, 10:00-13:00.
gio 4/7/24, Aula 13 SPV, 10:00-13:00.
gio 5/9/24, Aula 13 SPV, 10:00-13:00.
Appello straordinario: Monday 21/10/24, place: Sala Riunioni B203 DIAG Department (Via Ariosto 25, Rome). Hour: 09:00-12:00
Organization
Main website of the course: https://sites.google.com/a/uniroma1.it/danielaiacoviello/didattica
Schedule of the lessons: https://www.ingegneriagestionale.uniroma1.it/drupal/laureamagistrale/orario-delle-lezioni.
Lessons by Prof. Daniela Iacoviello on Monday.
I will do lesson on Thursday (12:00-14:00 Aula 15 San Pietro in Vincoli) and Friday (14:00-16:00 Aula 5 San Pietro in Vincoli).
Exam dates and modality: Written exam with exercises and questions. There is ONE exam, with exercises and questions on the two parts.
For Module 2, there will be one question on theory, plus one excercise in which the student will be asked to write the MPC mathematical formulation for a given problem. THE EXAM MUST BE BOOKED ON INFOSTUD.
Office hours: Thursdays, 11:30 to 13:00, in presence or online (meet.google.com/zob-fhvk-bsz). Please send me an email to book an appointment.
Program of Module 2
Introduction to Model Predictive Control (MPC). Hystorical notes. Pros and cons;
Formulation of an MPC problem: objective function, constraints, role and selection criteria for the stage cost, for the terminal cost, for the terminal constraints;
Analysis: recursive feasibility, optimality, stability.
Economic MPC. Differences wrt classic MPC and associated challenges;
MPC problems with mixed-integer variables and dynamical-locigal constraints. Examples.
Examples of applications in various sectors: industrial control, power systems, transportation, etc.
Introduction to combining MPC with reinforcement learning.
Implementation in Julia technical language (https://julialang.org/).
Course Material
LINK TO LECTURE SLIDES, CODE, MY NOTES AND OTHER CLASS MATERIALS
LINK TO FOLDER CONTAINING THE LIST OF THE LESSONS WITH MATERIAL (NOTES AND AUDIO RECORDING)
LINK TO DIARY OF THE LESSONS AND SUGGESTED READINGS. Notes and recordings of the lessons are available at the link above.
LINK TO MY NOTES WITH ADDITIONAL COMMENTS AND EXPLANATIONS FOR SOME OF THE LESSONS.
During the lessons I will indicate the exact study material to consult. In the followng you will find a preliminary list. I will strive to use only study material that is free and openly accessible over the internet.
REFERENCES (WILL BE UPDATED DURING THE COURSE)
Excellent books on MPC are:
[Cannon_2016]. Kouvaritakis, Basil, and Mark Cannon. "Model predictive control." Switzerland: Springer International Publishing (2016): 38.
https://www.springer.com/gp/book/9783319248516. Available here: https://www.academia.edu/28894969/Advanced_Textbooks_in_Control_and_Signal_Processing_Model_Predictive_Control_Basil_Kouvaritakis_Mark_Cannon_Classical_Robust_and_Stochastic
Rawlings, James Blake, David Q. Mayne, and Moritz Diehl. Model predictive control: theory, computation, and design. Vol. 2. Madison, WI: Nob Hill Publishing, 2017. Available online at: https://sites.engineering.ucsb.edu/~jbraw/mpc/MPC-book-2nd-edition-1st-printing.pdf
These are advanced books, we will use only specific sections, as I will mention during the course.
The following ones are some excellent articles on MPC.
[Bemporad_1999]. Bemporad , Alberto, and Manfred Morari . "Control of systems integrating logic, dynamics, and constraints." Automatica 35, no. 3 (1999): 407 427.
https://www.sciencedirect.com/science/article/abs/pii/S0005109898001782
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.35.2690&rep=rep1&type=pdf
[Mayne_2000]. Mayne, David Q., James B. Rawlings, Christopher V. Rao, and Pierre OM Scokaert. "Constrained model predictive control: Stability and optimality." Automatica 36, no. 6 (2000): 789-814.
https://www.sciencedirect.com/science/article/pii/S0005109899002149
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.231.3109&rep=rep1&type=pdf
[MIT_2003]. MIT Course “Optimization Methods in Management Science”. Available at this link.
See lecture notes at this link.
•I suggest checking in particular lessons L10 and L11.
•Read the IP reference guide (PDF).
[Hax_1977]. Bradley, Stephen P., Arnoldo C. Hax, and Thomas L. Magnanti. Applied mathematical programming. Addison-Wesley, 1977.
http://web.mit.edu/15.053/www/AMP.htm
•Consult Chapter 9.
Another interesting presentation on logical constraints and integer programming is at this link.
Reference for the application of MPC to traffic management.
[Liberati_2020]. Liberati, Francesco. "Model predictive control of a road junction." Smart Cities 3.3 (2020): 806-817.
https://www.mdpi.com/2624-6511/3/3/41
Reference for the application of MPC to assembly line control.
[Liberati_2021]. Liberati, Francesco. "Task Execution Control in an Assembly Line via Shrinking Horizon Model Predictive Control”. Password –protected file in the shared Google drive folder. The password has been sent via message on Google Class. Ask in case. Note: this file is confidential, for personal study only, it cannot be shared in any way.
Additional references on MPC for building energy management. These are not mandatory, but I suggest to have at least a quick read. Skip the parts we did not do at lesson. See the simulation sections to see how the MPC controller manages the loads, the generation and the storage of energy in the building:
[2014_Di Giorgio] Di Giorgio, Alessandro, and Francesco Liberati. "Near real time load shifting control for residential electricity prosumers under designed and market indexed pricing models." Applied Energy 128 (2014): 119-132.
https://www.sciencedirect.com/science/article/abs/pii/S0306261914003857
[2019_Liberati] Liberati, Francesco, et al. "Joint model predictive control of electric and heating resources in a smart building." IEEE Transactions on Industry Applications 55.6 (2019): 7015-7027.
https://ieeexplore.ieee.org/abstract/document/8786121/
[2018_Liberati] Liberati, Francesco, and Alessandro Di Giorgio. "Economic model predictive and feedback control of a smart grid prosumer node." Energies 11.1 (2018): 48.
https://www.mdpi.com/1996-1073/11/1/48
Past Module 2 (formerly Module 3) Exams
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