Data-Enabled Predictive Control: In the Shallows of the DeePC
By Jeremy Coulson, John Lygeros, Florian Dörfler. European Control Conference, 2018
815 citations recorded by the source corpus.
We consider the problem of optimal trajectory tracking for unknown systems. A novel data-enabled predictive control (DeePC) algorithm is presented that computes optimal and safe control policies using real-time feedback driving the unknown system along a desired trajectory while satisfying system constraints. Using a finite number of data samples from the unknown system, our proposed algorithm uses a behavioural systems theory approach to learn a non-parametric system model used to predict future trajectories. The DeePC algorithm is shown to be equivalent to the classical and widely adopted Model Predictive Control (MPC) algorithm in the case of deterministic linear time-invariant systems. In the case of nonlinear stochastic systems, we propose regularizations to the DeePC algorithm. Simulations are provided to illustrate performance and compare the algorithm with other methods.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/85cb8498da21cdedb7b06d0db9f3443cb754abaa
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In Control and Systems Engineering
- Lukas Hewing
- Melanie Nicole Zeilinger
- Frank Allgöwer
- Mehran Mesbahi
- M. Kanat Camlibel
- Kim Peter Wabersich
- Henk van Waarde
- Matthias Albrecht Müller
Citations in the corpus
- Data-Driven Model Predictive Control With Stability and Robustness Guarantees (2019, methodology): “After stating the required definitions and existing results in Section II, we expand the nominal MPC scheme of [20], [21] by terminal equality constraints in Section III.”
- Learning-Based Model Predictive Control: Toward Safe Learning in Control (2020, background): “4, including the information gain exploration–exploitation trade-off is therefore naturally u s e on l descriptions (as in 24, 25 ).”
- From Noisy Data to Feedback Controllers: Nonconservative Design via a Matrix S-Lemma (2020, background): “Thelatter lineofworkhasbeenquitefruitful,withcontributionsranging fromoutputmatching[34]andcontrolbyinterconnection[35], to data-enabled predictive control [36] and a data-based closed-loop system parameterization [37].”