Data-driven predictive control (DDPC) has been recently proposed as an effective alternative to traditional model-predictive control (MPC) for its unique ...
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Jul 3, 2023 · This work proposes a novel data-driven stochastic predictive control scheme for chance-constrained LTI systems subject to measurement noise and additive ...
Dec 23, 2023 · We propose a data-driven receding-horizon control method dealing with the chance-constrained output-tracking problem of unknown stochastic linear time- ...
Aug 4, 2020 · In this paper we propose a new method to design a GP-based NMPC algorithm for finite horizon control problems.
Dec 8, 2021 · We propose a novel data-driven stochastic predictive control scheme for chance-constrained LTI systems subject to measurement noise and additive stochastic ...
Aug 2, 2023 · In this paper, we propose a data-driven stochastic predictive control scheme for LTI systems subject to possibly unbounded additive process disturbances.
In this work, we propose a distributed stochastic model predictive control (DSMPC) scheme for dynamically coupled linear discrete-time systems subject to ...
Abstract. This paper investigates data-driven output-feedback predictive control of linear systems subject to stochastic disturbances.
Aug 2, 2023 · In the present paper, we aim to extend deterministic data-driven predictive control towards stochastic LTI systems affected by possibly ...
Dec 9, 2021 · We propose a novel data-driven stochastic model predictive control (MPC) algorithm to control linear time-invariant systems with additive ...