/ESE-619-Model-Predictive-Control

Lecture Slides, Personal Notes, Homework Solutions and Codes for ESE 619: Model Predictive Control 2023 Spring @ UPenn

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ESE-619-Model-Predictive-Control

Overview

Lecture Slides, Personal Notes, Homework Solutions and Codes for ESE 619: Model Predictive Control 2023 Spring @ UPenn

Reference Book:

  • Predictive Control for linear and hybrid systems, F. Borrelli, A. Bemporad, M. Morari, 2017 Cambridge University Press (link)
  • Model Predictive Control: Theory and Design, James B. Rawlings, David Q. Mayne and Moritz M. Diehl, 2nd Edition, 2022, Nob Hill Publishing (link)

Lecture Slides: (Slides)

  • First half semester (lecture 1-6): Review on basics of Linear System Thoery, Convex optimization, Optimal Control and Model Predictive Control
  • Second half semester (lecture 7-14): In-depth discussions on Linear and Hybrid MPC Theory, including: Stability, Feasibility, Practical Issues, Expliclit MPC, Hybrid MPC, Robust MPC and Numerical Optimization

Copyright of the slides belongs to Professor Manfred Morari and his collaborators.

Homework Assignments (Homework)

  • 7 homework assignments
  • HWX_code: MATLAB source code (live scripts) for each of the assignment
  • ESE_619_HWX_Wei-Cheng_Huang: Personal Solution for the homework, final grade: 449.5/450
  • To run the MATLAB code, you need to install the Multi-Parametric Toolbox (MPT3)

Personal Notes (Notes)

  • Personal notes for all 13 lectures on MPC (lecture 14 Numerical Optimization not included currently). Personal notes contain contents in the slides, supplementary materials from the textbooks, and discussions during lectures and office hours
  • Not guaranteed to be completely correct. Please contact me if you find any errors (typos, conceptual mistakes etc.) I would really appreciate your reading and correction

Special Comments

  • Spring 2023 is the last time Professor Morari taught this course. Learned so much from this world-leading control theorist. Always gained new understanding of both research and practice from him not only in the course, but also in those one-to-one private chats during the after-class office hours. Thank you, Manfred!

  • Also recommended: Professor Manfred Morari's Farewell Lecture at ETH in 2016: Computation and Uncertainty, Reflections on 40 Years of Control. He gave a similar farewell talk in the last lecture of the semester. Definitely worth reviewing over and over again.