Abstract
In this article, we extend discrete-time explicit model-predictive control (MPC) rigorously to linear distributed parameter systems. After formulating an MPC framework and giving a relevant Karush-Kuhn-Tucker theorem, we realize fast regionless explicit MPC by using the dual-active-set method QPKWIK. A Timoshenko beam with input and state constraints is used to demonstrate the efficacy of the design at controlling a continuous-time hyperbolic partial differential equation with constraints, using a discrete-time explicit MPC controller.
| Original language | English |
|---|---|
| Article number | 1 |
| Pages (from-to) | 518-525 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Automatic Control |
| Volume | 70 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2025 |
| MoE publication type | A1 Journal article-refereed |
Funding
The work of Jukka-Pekka Humaloja was supported in part by the Jenny and Antti Wihuri Foundation and in part by the Vilho, Yrj\u00F6 and Kalle V\u00E4is\u00E4l\u00E4 Foundation. The authors would like to gratefully acknowledge the input of the audience at the 2022 International Symposium on Mathematical Theory of Networks and Systems, and Prof. Martin M\u00F6nnigmann, Prof. Mark Cannon, Prof. Eric Kerrigan, and Prof. Tor Arne Johansen, for enlightening discussions during the preparation of this manuscript. An anonymous referee pointed out [27], leading to a major improvement of Theorem 5.
Keywords
- Costs
- Distributed parameter systems
- Hilbert space
- Linear systems
- Optimal control
- Optimization
- Predictive control
- Predictive control for linear systems
- Space exploration