Constrained Nonlinear Output Regulation Using Model Predictive Control
| Autor: | Matthias A. Müller, Johannes Koehler, Frank Allgöwer |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
0209 industrial biotechnology
Offset (computer science) Computer science Regulator 02 engineering and technology Positive-definite matrix Regularization (mathematics) Computer Science Applications Nonlinear system Model predictive control 020901 industrial engineering & automation Exponential stability Control and Systems Engineering Control theory Minimum phase Electrical and Electronic Engineering |
| Zdroj: | IEEE Transactions on Automatic Control. 67:2419-2434 |
| ISSN: | 2334-3303 0018-9286 |
| DOI: | 10.1109/tac.2021.3081080 |
| Popis: | We present a model predictive control (MPC) framework to solve the constrained nonlinear output regulation problem. The main feature of the proposed framework is that the application does not require the solution to classical regulator (Francis-Byrnes-Isidori) equations or any other offline design procedure. In particular, the proposed formulation simply minimizes the predicted output error, possibly with some input regularization. Instead of using terminal cost/sets or a positive definite stage cost as is standard in MPC theory, we build on the theoretical results by Grimm et al. 2005 using a detectability notion. The proposed formulation is applicable if the constrained nonlinear regulation problem is (strictly) feasible, the plant is incrementally stabilizable and incrementally input-output to state stable (i-IOSS/detectable). We show that for minimum phase systems such a design ensures exponential stability of the regulator manifold. We also provide a design procedure in case of unstable zero dynamics using an incremental input regularization and a nonresonance condition. The theoretical results are illustrated with an example involving offset free tracking. |
| Databáze: | OpenAIRE |
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