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Full text release has been delayed at the author's request until December 14, 2025

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A Comparative Study Between Dynamic Programming and Model Predictive Control for Closed-Loop Control

Adekoya, Oluwaseun
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1733835902814313

Abstract Details

2024, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
The development of dynamic systems (both physical plant and control systems) in a sequential manner often results in sub-optimal solutions. However, solutions obtained using combined physical and control system design methodologies have been observed to yield optimal solutions. The overarching interest in obtaining closed-loop solutions with decent computational cost requirements brings about the topic of interest - a comparison of two of the most popular methods employed to cater for this: Model Predictive Control and Dynamic Programming. If the primary requirement is real-time control with a need to handle constraints dynamically, Model Predictive Control (MPC) is the more practical choice. If the problem allows for offline computation and requires globally optimal solutions, and the state and action spaces are not extremely large, Dynamic Programming (DP) may be more practical. This work studies both methods with respect to accuracy, type of closed-loop feedback solutions, and computational efficiency. Both methods are incorporated within a nested control co-design formulation. To validate the accuracy of both techniques, their practical application is demonstrated through case studies involving a single link manipulator, a single pendulum-type crane, and a quarter car suspension system. Each case study includes a model description, problem formulation, and results obtained using both MPC and DP techniques. The findings highlight the effectiveness of nested formulations with feedback methods in achieving optimal control co-design, with comprehensive assessments of each approach.
Michael Alexander-Ramos, Ph.D. (Committee Chair)
Manish Kumar, Ph.D. (Committee Member)
David Thompson, Ph.D. (Committee Member)
90 p.
Mechanical Engineering
Model Predictive Control; Dynamic Programming; Closed loop Control; Control Co design; Design optimization; Dynamic Systems

Recommended Citations

Citations

  • Adekoya, O. (2024). A Comparative Study Between Dynamic Programming and Model Predictive Control for Closed-Loop Control [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1733835902814313

    APA Style (7th edition)

  • Adekoya, Oluwaseun. A Comparative Study Between Dynamic Programming and Model Predictive Control for Closed-Loop Control. 2024. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1733835902814313.

    MLA Style (8th edition)

  • Adekoya, Oluwaseun. "A Comparative Study Between Dynamic Programming and Model Predictive Control for Closed-Loop Control." Master's thesis, University of Cincinnati, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1733835902814313

    Chicago Manual of Style (17th edition)

ucin1733835902814313
© 2024, some rights reserved.Creative Commons License A Comparative Study Between Dynamic Programming and Model Predictive Control for Closed-Loop Control by Oluwaseun Adekoya is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.