Towards a "Turnkey" Model Predictive Controller

Steven Kuntz

For three decades, model predictive control (MPC) has been the flagship advanced control method in the chemical process industries. However, most implementations still use heuristic methods for designing MPC estimators, especially for offset-free MPC implementations.

A “turnkey” model predictive control (MPC) algorithm is a model-based controller that works out-of-the-box, with no tuning necessary. I developed system identification algorithms for integrating disturbance models, and have validated them in real-world applications [1]–[5]. I also established new stability results for MPC and offset-free MPC with plant-model mismatch [6]–[7].

References:

[1] S. J. Kuntz and J. B. Rawlings, “Maximum likelihood estimation of linear disturbance models for offset-free model predictive control,” in American Control Conference, Atlanta, GA, 2022, pp. 3961–3966. doi: https://doi.org/10.23919/ACC53348.2022.9867344.

[2] S. J. Kuntz, J. J. Downs, S. M. Miller, and J. B. Rawlings, An industrial case study on the combined identification and offset-free model predictive control of a chemical process, FOCAPO/CPC 2023, January 8-12, 2023, San Antonio, Texas, 2023.

[3] S. J. Kuntz, J. J. Downs, S. M. Miller, and J. B. Rawlings, “An industrial case study on the combined identification and offset-free control of a chemical process,” Computers & Chemical Engineering, vol. 179, p. 108 429, 2023. doi: https://doi.org/10.1016/j.compchemeng.2023.108429.

[4] S. J. Kuntz, J. J. Downs, S. M. Miller, and J. B. Rawlings, An industrial case study on the combined identification and offset-free control of a chemical process, AIChE Annual Meeting, Orlando, FL, 2023. url: https://aiche.confex.com/aiche/2023/meetingapp.cgi/Paper/674827.

[5] S. J. Kuntz and J. B. Rawlings. Maximum Likelihood Identification of Linear Models with Integrating Disturbances for Offset-Free Control. IEEE Trans. Auto. Cont., 2024. Submitted 6/5/2024, Revised 11/4/2024.

[6] S. J. Kuntz and J. B. Rawlings. Beyond inherent robustness: strong stability of MPC despite plant-model mismatch. IEEE Trans. Auto. Cont., 2025. Submitted 11/22/2024.

[7] S. J. Kuntz and J. B. Rawlings. Offset-free model predictive control: stability under plant-model mismatch. IEEE Trans. Auto. Cont., 2025. In progress.