Details
| Original language | English |
|---|---|
| Pages (from-to) | 6923-6930 |
| Number of pages | 8 |
| Journal | IFAC-PapersOnLine |
| Volume | 53 |
| Issue number | 2 |
| Publication status | Published - 2020 |
Abstract
Keywords
- eess.SY, cs.SY, Tracking, Data-based control, Predictive control
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
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In: IFAC-PapersOnLine, Vol. 53, No. 2, 2020, p. 6923-6930.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Data-Driven Tracking MPC for Changing Setpoints
AU - Berberich, Julian
AU - Köhler, Johannes
AU - Müller, Matthias A.
AU - Allgöwer, Frank
PY - 2020
Y1 - 2020
N2 - We propose a data-driven tracking model predictive control (MPC) scheme to control unknown discrete-time linear time-invariant systems. The scheme uses a purely data-driven system parametrization to predict future trajectories based on behavioral systems theory. The control objective is tracking of a given input-output setpoint. We prove that this setpoint is exponentially stable for the closed loop of the proposed MPC, if it is reachable by the system dynamics and constraints. For an unreachable setpoint, our scheme guarantees closed-loop exponential stability of the optimal reachable equilibrium. Moreover, in case the system dynamics are known, the presented results extend the existing results for model-based setpoint tracking to the case where the stage cost is only positive semidefinite in the state. The effectiveness of the proposed approach is illustrated by means of a practical example.
AB - We propose a data-driven tracking model predictive control (MPC) scheme to control unknown discrete-time linear time-invariant systems. The scheme uses a purely data-driven system parametrization to predict future trajectories based on behavioral systems theory. The control objective is tracking of a given input-output setpoint. We prove that this setpoint is exponentially stable for the closed loop of the proposed MPC, if it is reachable by the system dynamics and constraints. For an unreachable setpoint, our scheme guarantees closed-loop exponential stability of the optimal reachable equilibrium. Moreover, in case the system dynamics are known, the presented results extend the existing results for model-based setpoint tracking to the case where the stage cost is only positive semidefinite in the state. The effectiveness of the proposed approach is illustrated by means of a practical example.
KW - eess.SY
KW - cs.SY
KW - Tracking
KW - Data-based control
KW - Predictive control
UR - http://www.scopus.com/inward/record.url?scp=85105064254&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2020.12.389
DO - 10.1016/j.ifacol.2020.12.389
M3 - Article
VL - 53
SP - 6923
EP - 6930
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8963
IS - 2
ER -