## Dynamic Optimization

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Dynamic Optimization for Engineers is a graduate level course on the theory and applications of numerical methods for solution of time-varying systems with a focus on engineering design and real-time control applications. Concepts taught in this course include mathematical modeling, data reconciliation, reinforcement learning, nonlinear programming, estimation, and advanced control methods such as model predictive control.

Dynamic Optimization for Engineers is a graduate level course on the theory and applications of numerical methods for solution of time-varying systems with a focus on engineering design and real-time control applications. Concepts taught in this course include mathematical modeling, data reconciliation, machine learning, nonlinear programming, estimation, and advanced control methods such as model predictive control.

Dynamic Optimization for Engineers is a graduate level course on the theory and applications of numerical methods for solution of time-varying systems with a focus on engineering design and real-time control applications. Concepts taught in this course include mathematical modeling, data reconciliation, nonlinear programming, estimation, and advanced control methods such as model predictive control.

Dynamic Optimization for Engineers is a graduate level course on the theory and applications of numerical methods for solution of time-varying systems with a focus on engineering design and real-time control applications. Concepts taught in this course include mathematical modeling, data reconciliation, reinforcement learning, nonlinear programming, estimation, and advanced control methods such as model predictive control.

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Instructions are also available to build a simplified (SISO) lab kit with an Arduino and bread-board ($49 for recommended parts).

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<option value="Basic (PID) and Advanced Control (MPC) Kit">Basic (PID) and Advanced Control (MPC) Kit $35.00 USD</option> <option value="Basic (PID) Lab Kit">Basic (PID) Lab Kit $29.00 USD</option>

</select> </td></tr> <tr><td><input type="hidden" name="on1" value="Firmware (can change later)">Arduino Firmware (can change later)</td></tr><tr><td><select name="os1">

<option value="MATLAB and Simulink">MATLAB and Simulink </option> <option value="Python">Python </option>

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If you suspect or are aware that you have a disability, you are strongly encouraged to contact the University Accessibility Center (UAC) located at 2170 WSC (801-422-2767) as soon as possible. A disability is a physical or mental impairment that substantially limits one or more major life activities. Examples include vision or hearing impairments, physical disabilities, chronic illnesses, emotional disorders (e.g., depression, anxiety), learning disorders, and attention disorders (e.g., ADHD). When registering with the UAC, the disability will be evaluated and eligible students will receive assistance in obtaining reasonable University approved accommodations.

If you suspect or are aware that you have a disability, you are strongly encouraged to contact the University Accessibility Center (UAC) located at 2170 WSC (801-422-2767) as soon as possible. A disability is a physical or mental impairment that substantially limits one or more major life activities. Examples include vision or hearing impairments, physical disabilities, chronic illnesses, emotional disorders (e.g., depression, anxiety), learning disorders, and attention disorders (e.g., ADHD). When registering with the UAC, the disability will be evaluated and eligible students will receive assistance in obtaining reasonable University approved accommodations.

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Class Participation

Assignments

Article Review

Mid-Term Exam

5%

25%

Assignments

Final Exam

10%

25%

Mid-Term Exam

Arduino Project

20%

10%

Final Exam

Final Project

25% (:cellnr:) Arduino Project (:cell:) 5% (:cellnr:) Final Project (:cell:) 25%

30%

**A** Read material in advance, be attentive and ask questions in lectures, understand and do all homework on time, study hard for exams well before the exam starts, work hard and perform well on exams and the class projects.

**A** Read or watch material in advance, be attentive and ask questions in lectures, understand and do all homework on time, study hard for exams well before the exam starts, work hard and perform well on exams and the class projects.

You will be required to complete a course projects. I will provide suggestions or you can do something of your own interest or something that is integrated with a campus or off-campus research project.

You will be required to complete a course project. I will provide suggestions or you can do something of your own interest or something that is integrated with a campus or off-campus research project.

A Temperature Control Lab (PID+MPC) is required for several exercises in this course. The lab kits are available for bulk order ($25/kit) or individual order ($35/kit). Instructions are also available to build a simplified (SISO) lab kit with an Arduino and bread-board ($49 for recommended parts).

A Temperature Control Lab (PID+MPC) is required for several exercises in this course. The lab kits are available for bulk order ($25/kit) or individual order ($35/kit).

Instructions are also available to build a simplified (SISO) lab kit with an Arduino and bread-board ($49 for recommended parts).

<option value="Basic (PID) and Advanced Control (MPC) Kit">Basic (PID) and Advanced Control (MPC) Kit $35.00 USD</option>

<option value="Basic (PID) and Advanced Control (MPC) Kit">Basic (PID) and Advanced Control (MPC) Kit $35.00 USD</option>

A Temperature Control Lab (PID+MPC) is required for several exercises in this course. The lab kits are available for bulk order ($25/kit) or individual order ($35/kit). Instructions are also available to build a simplified (SISO) lab kit with an Arduino and bread-board ($49 for recommended parts).

A Temperature Control Lab (PID+MPC) is required for several exercises in this course. The lab kits are available for bulk order ($25/kit) or individual order ($35/kit). Instructions are also available to build a simplified (SISO) lab kit with an Arduino and bread-board ($49 for recommended parts).

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<option value="Basic (PID) Lab Kit">Basic (PID) Lab Kit $29.00 USD</option> <option value="Basic (PID) and Advanced Control (MPC) Kit">Basic (PID) and Advanced Control (MPC) Kit $35.00 USD</option>

</select> </td></tr> <tr><td><input type="hidden" name="on1" value="Firmware (can change later)">Arduino Firmware (can change later)</td></tr><tr><td><select name="os1">

<option value="MATLAB and Simulink">MATLAB and Simulink </option> <option value="Python">Python </option>

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#### Required Text

#### Course Requirements

To register for the course, fill out a Personal Information Sheet.

Office: 801-422-2590, 350R CB

Office: 801-422-2590, 350 CB

Final Project

Arduino Project

30%

5% (:cellnr:) Final Project (:cell:) 25%

- ChE436: Process Dynamics and Control in Python (2016-)

- ChE436: Process Dynamics and Control in Python (2016-current)

- ChE436: Process Dynamics and Control for review on dynamic modeling and control

- ChE436: Process Dynamics and Control in MATLAB (2011-2015)
- ChE436: Process Dynamics and Control in Python (2016-)

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#### Preventing Sexual Misconduct

As required by Title IX of the Education Amendments of 1972, the university prohibits sex discrimination against any participant in its education programs or activities. Title IX also prohibits sexual harassment—including sexual violence—committed by or against students, university employees, and visitors to campus. As outlined in university policy, sexual harassment, dating violence, domestic violence, sexual assault, and stalking are considered forms of “Sexual Misconduct” prohibited by the university.

University policy requires any university employee in a teaching, managerial, or supervisory role to report incidents of Sexual Misconduct that come to their attention through various forms including face-to-face conversation, a written class assignment or paper, class discussion, email, text, or social media post. If you encounter Sexual Misconduct, please contact the Title IX Coordinator at t9coordinator@byu.edu or 801-422-2130 or Ethics Point at https://titleix.byu.edu/report-concern or 1-888-238-1062 (24-hours). Additional information about Title IX and resources available to you can be found at titleix.byu.edu.

- Discussion Group: https://groups.google.com/forum/#!forum/apmonitor
- YouTube Channel: https://www.youtube.com/user/APMonitorCom (subscribe)

- Discussion Group: https://groups.google.com/forum/#!forum/apmonitor

- Discussion Group: https://groups.google.com/forum/#!forum/apmonitor

Class Preparation and Participation

Class Participation

Assignments

Article Review

10%

5%

Mid-Term Exam

Assignments

20%

10%

Final Exam

Mid-Term Exam

30%

20% (:cellnr:) Final Exam (:cell:) 25%

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(:cellnr:)

Assignments / Participation

Class Preparation and Participation

20%

10% (:cell:) Assignments (:cell:) 10%

ChE 593R: Dynamic OptimizationM/W/F 1-3 pm

#### Course Introduction

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ChE 693R: Dynamic Optimization

ChE 593R: Dynamic Optimization

M/W/F ? am, ?413? CB

M/W/F 1-3 pm, 413? CB

(:title Dynamic Optimization for Engineers:)

(:title Dynamic Optimization:)

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(:cell width=2% align='right':) (:cell width=83%:)

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- ChE436: Process Dynamics and Control for review on dynamic modeling and control

- ChE436: Process Dynamics and Control for review on dynamic modeling and control

- Computational Tools for Engineers for review on MATLAB / Python
- Optimization Techniques in Engineering for review on optimization
- Process Dynamics and Control for review on dynamic modeling and control

- ChE263: Computational Tools for Engineers for review on MATLAB / Python
- ME575: Optimization Techniques in Engineering for review on optimization
- ChE436: Process Dynamics and Control for review on dynamic modeling and control

- Courses
- Computational Tools for Engineers for review on MATLAB / Python
- Optimization Techniques in Engineering for review on optimization
- Process Dynamics and Control for review on dynamic modeling and control

- Optimization Methods for Engineering Design, Parkinson, A.R., Balling, R., and J.D. Hedengren. Available at: https://apmonitor.com/me575/index.php/Main/BookChapters

- Optimization Methods for Engineering Design, Parkinson, A.R., Balling, R., and J.D. Hedengren, 2013. Available at: https://apmonitor.com/me575/index.php/Main/BookChapters

- Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Hedengren, J. D. and Asgharzadeh Shishavan, R., Powell, K.M., and Edgar, T.F., Computers and Chemical Engineering, Volume 70, pg. 133–148, 2014. Available

- Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Hedengren, J. D. and Asgharzadeh Shishavan, R., Powell, K.M., and Edgar, T.F., Computers and Chemical Engineering, Volume 70, pg. 133–148, 2014. Available at: https://dx.doi.org/10.1016/j.compchemeng.2014.04.013

at: https://dx.doi.org/10.1016/j.compchemeng.2014.04.013

- Optimization Methods for Engineering Design, Parkinson, A.R., Balling, R., and J.D. Hedengren. Available at: https://apmonitor.com/me575/index.php/Main/BookChapters
- Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Hedengren, J. D. and Asgharzadeh Shishavan, R., Powell, K.M., and Edgar, T.F., Computers and Chemical Engineering, Volume 70, pg. 133–148, 2014. Available at: https://dx.doi.org/10.1016/j.compchemeng.2014.04.013
- Optimization of Chemical Processes, Edgar, T.F., Himmelblau, D.M., and L.S. Lasdon, McGraw Hill, 2001.

- Online Resources
- Discussion Group: https://groups.google.com/forum/#!forum/apmonitor
- YouTube Channel: https://www.youtube.com/user/APMonitorCom (subscribe)

- Articles
- Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Hedengren, J. D. and Asgharzadeh Shishavan, R., Powell, K.M., and Edgar, T.F., Computers and Chemical Engineering, Volume 70, pg. 133–148, 2014. Available

- Books
- Optimization Methods for Engineering Design, Parkinson, A.R., Balling, R., and J.D. Hedengren. Available at: https://apmonitor.com/me575/index.php/Main/BookChapters

at: https://dx.doi.org/10.1016/j.compchemeng.2014.04.013

- Optimization of Chemical Processes, Edgar, T.F., Himmelblau, D.M., and L.S. Lasdon, McGraw Hill, 2001.

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(:cell width=80%:) John Hedengren worked 5 years with ExxonMobil Chemical on Optimization solutions for the petrochemical industry. He conducts research in optimization methods, modeling systems, and applications in Chemical Engineering. The PRISM group is actively working on oil and gas drilling automation, reservoir engineering, process optimization, unmanned aerial vehicles, and systems biology. (:tableend:)

#### Chemical Engineering 693R

Dynamic Optimization

ChE 693R: Dynamic Optimization

#### Professor:

#### Professor

John Hedengren worked 5 years with ExxonMobil Chemical on Optimization solutions for the petrochemical industry. He conducts research in optimization methods, modeling systems, and applications in Chemical Engineering. The PRISM group is actively working on oil and gas drilling automation, reservoir engineering, process optimization, unmanned aerial vehicles, and systems biology.

John Hedengren worked 5 years with ExxonMobil Chemical on Optimization solutions for the petrochemical industry. He conducts research in optimization methods, modeling systems, and applications in Chemical Engineering. The PRISM group is actively working on oil and gas drilling automation, reservoir engineering, process optimization, unmanned aerial vehicles, and systems biology.

#### Teaching Assistant

#### Computers

Using computer software as a technique for solving dynamic optimization problems is the focus of this course. All homework assignments will require the use of a computer.

#### Recitation Sessions

As needed through-out the semester. The Teaching Assistant will conduct the recitation sessions. Generally they will be held:

- Before exams
- To help work through difficult project issues
- For additional class time

Using computer software as a technique for solving dynamic optimization problems is the focus of this course. All homework assignments will require the use of a computer.

To address this concern, I have prepared software tutorials that assume very little knowledge of programming. There are also many excellent resources on the internet that give tutorial introductions to programming. Those students who have no or little programming experience can review these step-by-step instructional videos to gain some of the required background. We can also hold recitation sessions in a computer lab outside of normal class times if there is need.

This is an optimization course, not a programming course, but some familiarity with MATLAB, Python, C++, or equivalent programming language is required to perform assignments, projects, and exams. Students who complete the course will gain experience in at least one of these programming languages.

I will come prepared to each class, ready to help explain the material covered in the reading. I appreciate attentive students who respect my time and the time of other students.

To address this concern, I have prepared software tutorials that assume very little knowledge of programming. There are also many excellent resources on the internet that give tutorial introductions to programming. Those students who have no or little programming experience can review these step-by-step instructional videos to gain some of the required background.

This is a dynamic optimization course, not a programming course, but some familiarity with MATLAB, Python, or equivalent programming language is required to perform assignments, projects, and exams. Students who complete the course will gain experience in at least one programming language.

(:Summary:The default home page for the PmWiki distribution:) Welcome to PmWiki!

A local copy of PmWiki's documentation has been installed along with the software, and is available via the documentation index.

To continue setting up PmWiki, see initial setup tasks.

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(:title Dynamic Optimization for Engineers:) (:keywords nonlinear control, dynamic estimation, parameter estimation, dynamic optimization, engineering optimization, MATLAB, Python, differential, algebraic, modeling language, university course:) (:description Dynamic Optimization Course for Engineers at Brigham Young University:)

#### Chemical Engineering 693R

Dynamic OptimizationM/W/F ? am, ?413? CB

Dynamic Optimization for Engineers is a graduate level course on the theory and applications of numerical methods for solution of time-varying systems with a focus on engineering design and real-time control applications. Concepts taught in this course include mathematical modeling, data reconciliation, nonlinear programming, estimation, and advanced control methods such as model predictive control.

#### Professor:

John D. HedengrenOffice: 801-422-2590, 350R CB Cell: 801-477-7341 Contact: john.hedengren [at] byu.edu

#### Course Introduction

(:html:) (:htmlend:)

#### Teaching Assistant

#### Required Text

We will use a set of course notes and instructional videos that take the place of the book. Everyone will have access to these notes and videos through this web-site.

#### Resources

Reading is essential to success in this course. There are a number of resources that are available on the course web-site or through external sources. Most of the reading will come from journal articles or book chapters. Below is a list of some supplementary resources.

- Nonlinear Modeling, Estimation and Predictive Control in APMonitor, Hedengren, J. D. and Asgharzadeh Shishavan, R., Powell, K.M., and Edgar, T.F., Computers and Chemical Engineering, Volume 70, pg. 133–148, 2014. Available at: https://dx.doi.org/10.1016/j.compchemeng.2014.04.013
- Optimization of Chemical Processes, Edgar, T.F., Himmelblau, D.M., and L.S. Lasdon, McGraw Hill, 2001.

#### Computers

Using computer software as a technique for solving dynamic optimization problems is the focus of this course. All homework assignments will require the use of a computer.

#### Recitation Sessions

As needed through-out the semester. The Teaching Assistant will conduct the recitation sessions. Generally they will be held:

- Before exams
- To help work through difficult project issues
- For additional class time

#### Grading

(:table border=0 width=50%:) (:cell:) Homework (:cell:) 20% (:cellnr:) Mid-Term Exam (:cell:) 20% (:cellnr:) Final Exam (:cell:) 30% (:cellnr:) Final Project (:cell:) 30% (:tableend:)

**Grade** Expectations

**A** Read material in advance, be attentive and ask questions in lectures, understand and do all homework on time, study hard for exams well before the exam starts, work hard and perform well on exams and the class projects.

**B** Skim material in advance, attend lectures and try to stay awake, depend on TA for homework help, casually study for the exam by working the practice exam instead of learning concepts.

**C** Never read book, work on other homework during class, skip some homework assignments, start cramming for the exam the night before the exam.

**D** Skip class, don't turn in homework or turn it in late, start learning during the exam.

#### Exams

There will be a mid-term and the final exam. These exams may be closed book and/or open book, in-class or in the testing center, as specified by the instructor prior to the exam. Exams will only be given after the scheduled date by special permission. Students with conflicts should arrange to take the exam prior to the scheduled date.

#### Projects

You will be required to complete a course projects. I will provide suggestions or you can do something of your own interest or something that is integrated with a campus or off-campus research project.

#### Computer Tools

One of the most common questions that I receive from students who would like to take this class is, "How much programming experience is required to succeed in the class?"

To address this concern, I have prepared software tutorials that assume very little knowledge of programming. There are also many excellent resources on the internet that give tutorial introductions to programming. Those students who have no or little programming experience can review these step-by-step instructional videos to gain some of the required background. We can also hold recitation sessions in a computer lab outside of normal class times if there is need.

This is an optimization course, not a programming course, but some familiarity with MATLAB, Python, C++, or equivalent programming language is required to perform assignments, projects, and exams. Students who complete the course will gain experience in at least one of these programming languages.

I will come prepared to each class, ready to help explain the material covered in the reading. I appreciate attentive students who respect my time and the time of other students.

#### Disability Resources

If you suspect or are aware that you have a disability, you are strongly encouraged to contact the University Accessibility Center (UAC) located at 2170 WSC (801-422-2767) as soon as possible. A disability is a physical or mental impairment that substantially limits one or more major life activities. Examples include vision or hearing impairments, physical disabilities, chronic illnesses, emotional disorders (e.g., depression, anxiety), learning disorders, and attention disorders (e.g., ADHD). When registering with the UAC, the disability will be evaluated and eligible students will receive assistance in obtaining reasonable University approved accommodations.