Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2019 18th European Control Conference (ECC) |
| Untertitel | Proceedings |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 793-798 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 978-3-907144-00-8 |
| ISBN (Print) | 978-1-7281-1314-2 |
| Publikationsstatus | Veröffentlicht - Juni 2019 |
| Veranstaltung | 2019 European Control Conference (ECC) - Naples, Italien Dauer: 25 Juni 2019 → 28 Juni 2019 |
Abstract
In this paper, we present a simple methodology to design nonlinear robust output-feedback model predictive control (MPC) schemes. The design procedure is applicable to a large class of nonlinear systems and guarantees constraint satisfaction despite noise and disturbances. We utilize an existing observer with guaranteed exponential stability properties in combination with an initial bound on the estimation error in order to predict valid bounds on the possible future estimation error. The predicted estimation error is then used online to appropriately tighten the state and input constraints, using recently developed nonlinear robust MPC methods based on incremental stabilizability properties. The resulting nonlinear robust output-feedback MPC scheme is simple to implement, only marginally increases the computational demand (compared to a nominal MPC scheme), and ensures robust constraint satisfaction and input-to-state stability w.r.t. disturbances/noise. We demonstrate the simplicity and applicability of the proposed approach with a numerical example.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Steuerung und Optimierung
- Physik und Astronomie (insg.)
- Instrumentierung
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2019 18th European Control Conference (ECC): Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. S. 793-798 8795965.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung
}
TY - GEN
T1 - A simple framework for nonlinear robust output-feedback MPC
AU - Kohler, Johannes
AU - Muller, Matthias A.
AU - Allgöwer, Frank
N1 - Funding information: The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Research Training Group Soft Tissue Robotics (GRK 2198/1).
PY - 2019/6
Y1 - 2019/6
N2 - In this paper, we present a simple methodology to design nonlinear robust output-feedback model predictive control (MPC) schemes. The design procedure is applicable to a large class of nonlinear systems and guarantees constraint satisfaction despite noise and disturbances. We utilize an existing observer with guaranteed exponential stability properties in combination with an initial bound on the estimation error in order to predict valid bounds on the possible future estimation error. The predicted estimation error is then used online to appropriately tighten the state and input constraints, using recently developed nonlinear robust MPC methods based on incremental stabilizability properties. The resulting nonlinear robust output-feedback MPC scheme is simple to implement, only marginally increases the computational demand (compared to a nominal MPC scheme), and ensures robust constraint satisfaction and input-to-state stability w.r.t. disturbances/noise. We demonstrate the simplicity and applicability of the proposed approach with a numerical example.
AB - In this paper, we present a simple methodology to design nonlinear robust output-feedback model predictive control (MPC) schemes. The design procedure is applicable to a large class of nonlinear systems and guarantees constraint satisfaction despite noise and disturbances. We utilize an existing observer with guaranteed exponential stability properties in combination with an initial bound on the estimation error in order to predict valid bounds on the possible future estimation error. The predicted estimation error is then used online to appropriately tighten the state and input constraints, using recently developed nonlinear robust MPC methods based on incremental stabilizability properties. The resulting nonlinear robust output-feedback MPC scheme is simple to implement, only marginally increases the computational demand (compared to a nominal MPC scheme), and ensures robust constraint satisfaction and input-to-state stability w.r.t. disturbances/noise. We demonstrate the simplicity and applicability of the proposed approach with a numerical example.
UR - http://www.scopus.com/inward/record.url?scp=85071577764&partnerID=8YFLogxK
U2 - 10.23919/ECC.2019.8795965
DO - 10.23919/ECC.2019.8795965
M3 - Conference contribution
SN - 978-1-7281-1314-2
SP - 793
EP - 798
BT - 2019 18th European Control Conference (ECC)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 European Control Conference (ECC)
Y2 - 25 June 2019 through 28 June 2019
ER -