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Paper Citation Record · LEDGER

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2505.24572.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.24572 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:24:03.669417Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

  • verified exact7
  • verified fuzzy47
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd67b821-7a82-48fc-a81f-2b047d8e9060 · outbound

This paper cites Ensemble Control for Stochastic Systems with Asymmetric Laplace Noises.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Ensemble Control for Stochastic Systems with Asymmetric Laplace Noises

Reference 2

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verified exact
local_arxiv, observed 2026-08-07T12:24:04.893965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 04202b26-473f-4963-9187-12263c3ee32b · outbound

This paper cites De- centralized backstepping control for interconnected systems with non- triangular structural uncertainties.IEEE Transactions on Automatic Control, 68(3):1692–1699, 2023.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning De- centralized backstepping control for interconnected systems with non- triangular structural uncertainties.IEEE Transactions on Automatic Control, 68(3):1692–1699, 2023

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1bd2e93a-515d-4c4b-ad5e-7269e4c7d2bf · outbound

This paper cites Robust quadratic optimal control of linear systems with ellipsoid-set learning.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Robust quadratic optimal control of linear systems with ellipsoid-set learning

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation ba6a4cce-6e00-4176-b827-516303aaac22 · outbound

This paper cites A nonlinear MPC scheme for output tracking without terminal ingredients.IEEE Transactions on Automatic Control, 68(4):2368–2375, 2023.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning A nonlinear MPC scheme for output tracking without terminal ingredients.IEEE Transactions on Automatic Control, 68(4):2368–2375, 2023

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:14.701241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.035449Z digest=sha256:440fdcbfd8dca5d1752265f4ac880f62afe751f1c2c7ed5c18fbad857ea36bd1

Observation 2e062b68-7035-4833-bc3e-b704d77117d4 · outbound

This paper cites Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties.IEEE Transactions on Automatic Control, 69(11):8096–8103, 2024.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties.IEEE Transactions on Automatic Control, 69(11):8096–8103, 2024

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.104169Z digest=sha256:05fbf5e47e80d0bef9b8dfeece4bd790b96b46b002ab6f1d83f5819444731664

Observation 34fdea55-cc5a-43e8-870e-4c528949b015 · outbound

This paper cites Adaptive dual control with online outlier detection for uncertain systems.ISA transactions, 129:157–168, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Adaptive dual control with online outlier detection for uncertain systems.ISA transactions, 129:157–168, 2022

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.163962Z digest=sha256:b72fc7c1bced2c23fa9bfe70a147ad11989cd1350d550f541afc9541aa3c5e21

Observation 769f3882-b0b6-45b2-84f4-b33b33f47469 · outbound

This paper cites Adaptive quantile control for stochastic system.ISA transactions, 123:110–121, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Adaptive quantile control for stochastic system.ISA transactions, 123:110–121, 2022

Reference 8

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.233014Z digest=sha256:4c138cb98afee2ebf3536a9256167b63cf6f9f738f3a872e4607987126bb1010

Observation 12ed5e16-371c-4051-9bdc-9073ea6bde43 · outbound

This paper cites Active learning for anti-disturbance dual control of unknown nonlinear systems.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Active learning for anti-disturbance dual control of unknown nonlinear systems

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:24:04.732911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.281450Z digest=sha256:8b7f529c411e3b66065447020190373e42f6560133b429ffece5638123552df7

Observation 3900cbe2-5d90-437e-b7b1-137fc08d2b0a · outbound

This paper cites Dual control for stochastic systems with multiple uncertainties.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Dual control for stochastic systems with multiple uncertainties

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.346917Z digest=sha256:96db5b4281453c773220dcdb9855cf1e420b8b82a64ce79d239e8771282f70c3

Observation 08ef9326-c4aa-4add-9566-1c9e0430aee8 · outbound

This paper cites Data-driven optimization framework for nonlinear model predictive control.Mathematical Problems in Engineering, 2017(1):9402684, 2017.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Data-driven optimization framework for nonlinear model predictive control.Mathematical Problems in Engineering, 2017(1):9402684, 2017

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 48185fe4-8ee1-4dbb-837c-cfa84509c1ba · outbound

This paper cites Nonlinear prediction model for ventilation of ball mill pulverizing system.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Nonlinear prediction model for ventilation of ball mill pulverizing system

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.481694Z digest=sha256:701183b3791f7025ce3cd74cd5202eef07c3d8c041ea615ae52d13153140b9e8

Observation 59cd2b8b-6ea1-46d1-92d5-f79324b77322 · outbound

This paper cites A nonlinear model predictive controller based on the linguistic model for biochemical continuous sterilization.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning A nonlinear model predictive controller based on the linguistic model for biochemical continuous sterilization

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 38b188c5-d573-4024-81da-6bc693df82cd · outbound

This paper cites Energy- efficient dynamic matrix control for biochemical continuous sterilization.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Energy- efficient dynamic matrix control for biochemical continuous sterilization

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:13.516185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f2181104-9f40-4890-8b8a-57dd4dc2db6e · outbound

This paper cites A predictive controller with self-renewal model observer for continuous sterilization of biochemical process.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning A predictive controller with self-renewal model observer for continuous sterilization of biochemical process

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.694254Z digest=sha256:e350b97a180351580b672866e19c89bbebe2362c5d51c16db364d2002f615a71

Observation c7c7c104-f2e1-4229-b316-a0659dd732b2 · outbound

This paper cites Distributed stochastic model predictive control for cyber–physical systems with multiple state delays and probabilistic saturation constraints.Automatica, 129:109574, 2021.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Distributed stochastic model predictive control for cyber–physical systems with multiple state delays and probabilistic saturation constraints.Automatica, 129:109574, 2021

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 48a5e525-bbb4-4474-ba3d-d321a323d3d0 · outbound

This paper cites Control strategy for biopharmaceu- tical production by model predictive control.Biotechnology Progress, 40(2):e3426, 2024.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Control strategy for biopharmaceu- tical production by model predictive control.Biotechnology Progress, 40(2):e3426, 2024

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 6a8991a4-1513-44f3-8dec-b8151fcee110 · outbound

This paper cites Distributionally robust chance constrained data-enabled predictive control.IEEE Trans- actions on Automatic Control, 67(7):3289–3304, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Distributionally robust chance constrained data-enabled predictive control.IEEE Trans- actions on Automatic Control, 67(7):3289–3304, 2022

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:00.932155Z digest=sha256:b23a8f8b48c87d8e0cf67644cdfdb32bef1d8fe7815d4b828d9538b3a467c09a

Observation 6ac31870-ec1e-4851-b83e-44e41d605e93 · outbound

This paper cites Ramirez-Mendoza, and Yang Xu.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Ramirez-Mendoza, and Yang Xu

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:12.443770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.000834Z digest=sha256:e353f627aad55e2a2f592fad20fee1d373ea116fa8b2e3056e05cfc06306d901

Observation 1d86051c-2a44-405a-8901-9ac43bf4e9cb · outbound

This paper cites van Waarde, Jaap Eising, Harry L.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning van Waarde, Jaap Eising, Harry L

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 5782d80d-519c-447e-9668-5d49d384d906 · outbound

This paper cites Adaptive Fault-tolerant Control of Underwater Vehicles with Thruster Failures.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Adaptive Fault-tolerant Control of Underwater Vehicles with Thruster Failures

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:24:04.611983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.140787Z digest=sha256:6931cb110f58a8bc79f222009990c62b40bc841a633f4541f866901e71cabcbb

Observation 520e3a5f-1fe6-47fc-9771-83c5002471b6 · outbound

This paper cites A bionic data-driven approach for long-distance underwater navigation with anomaly resistance.IEEE Transactions on Instrumentation and Measurement, 74:1–14, 2025.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning A bionic data-driven approach for long-distance underwater navigation with anomaly resistance.IEEE Transactions on Instrumentation and Measurement, 74:1–14, 2025

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.214860Z digest=sha256:a78895c835dd728f34beac87596b329e753dc38eaaa8565a4ba40174d2bd4f0a

Observation c30ea80c-b8b8-4e83-b325-4a544380a756 · outbound

This paper cites Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:24:04.399680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.284134Z digest=sha256:97472001e6cd8465547608b8418e0571db1d9fbc83da5f90d894f8a0af9e3a49

Observation 8e760e7b-3073-4c89-8d59-fae46190e158 · outbound

This paper cites Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:24:04.189511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.321367Z digest=sha256:8574e9012822f211fc6faddbddb06ed04a71de76589e29c4b58d012c80364334

Observation ea5964f5-886f-45b2-a910-5f1869a4fa5b · outbound

This paper cites Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:24:04.041571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.378953Z digest=sha256:30b6ce9f1e348027e3a9935e85a10fa29b49c511db90f3010fa3c03afe187f16

Observation 443f29ac-41d6-4b32-bd53-6fb784ac4e5e · outbound

This paper cites The impact of integration of renewable energy on imbalance settlement: Resilience analysis.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning The impact of integration of renewable energy on imbalance settlement: Resilience analysis

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.441238Z digest=sha256:bb3a846a542a653d11aec13dfd5d38a5a696f5291d1a2d22f65194059bbd41c5

Observation 5dd76300-6d43-4115-9101-7a5cf1715937 · outbound

This paper cites Extended vehicle energy dataset (eVED): an enhanced large-scale dataset for deep learning on vehicle trip energy consumption.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Extended vehicle energy dataset (eVED): an enhanced large-scale dataset for deep learning on vehicle trip energy consumption

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:24:01.505468Z digest=sha256:8973191ef949f25d0d851e3cc674214b56f540343994ea1e3dad3c8569d2e7f5

Observation f94292b7-c297-45d6-8707-b2921d35fe89 · outbound

This paper cites An energy consumption model for electrical vehicle networks via extended federated-learning.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning An energy consumption model for electrical vehicle networks via extended federated-learning

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:11.997305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.582117Z digest=sha256:1bf65430227f1719c7a5e6b68e16a1337265a069f4b4ba59e84c80d0413624cb

Observation fe8c570c-1931-4846-9783-0074ba616736 · outbound

This paper cites Willems, I.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Willems, I

Reference 29

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raw_fallback, observed 2026-08-07T12:24:11.686196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f51c58df-8a3e-406d-9cc9-b1179ca2411b · outbound

This paper cites an unresolved cited work.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Unresolved cited work

Reference 30

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.681154Z digest=sha256:fb8c6ecedf8093fbf2219936eb7d027c1a817c17ed58aa840ab509d4517d3ba0

Observation 4d1c8228-c8fc-4683-8898-5f0793bd04fc · outbound

This paper cites Data-driven simulation and control.International Journal of Control, (12), 2008.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Data-driven simulation and control.International Journal of Control, (12), 2008

Reference 31

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raw_fallback, observed 2026-08-07T12:24:11.298790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.758116Z digest=sha256:91503dc7c3993033c82be356bdf1afeba700ad42b25591e89b6ed6b6b0dba528

Observation 581d0c3a-8a7b-443d-8acc-4d6b204a337c · outbound

This paper cites A missing data approach to data-driven filtering and control.IEEE Transactions on Automatic Control, 62(4):1972–1978, 2017.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning A missing data approach to data-driven filtering and control.IEEE Transactions on Automatic Control, 62(4):1972–1978, 2017

Reference 32

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raw_fallback, observed 2026-08-07T12:24:11.155262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.809677Z digest=sha256:8d532c0393749eec623aee7b3b92eef486c2eef504da571c8903f29925e35fbe

Observation bd34be37-91b8-4461-b36e-492fce23a6d1 · outbound

This paper cites Behavioral systems theory in data-driven analysis, signal processing, and control.Annual Reviews in Control, 52:42–64, 2021.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Behavioral systems theory in data-driven analysis, signal processing, and control.Annual Reviews in Control, 52:42–64, 2021

Reference 33

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raw_fallback, observed 2026-08-07T12:24:10.876875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.854990Z digest=sha256:e444f4557d5fac094fc626a3ccc9f4bec6fcdbb8f7add2c1767c020014f55c37

Observation 6806b59f-8cd3-4895-afe6-c777eea072eb · outbound

This paper cites Data-driven dynamic interpolation and approximation.Automatica, 135:110008, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Data-driven dynamic interpolation and approximation.Automatica, 135:110008, 2022

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:10.716843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.910403Z digest=sha256:53b1669df0a72890a0ea292ee47b2097594c5c6eb39fb95aadfe1a0c1aa2871d

Observation e64c1b42-0b82-4a07-8109-aa298077d564 · outbound

This paper cites Robust and kernelized data-enabled predictive control for nonlinear systems.IEEE Transac- tions on Control Systems Technology, 32(2):611–624, 2024.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Robust and kernelized data-enabled predictive control for nonlinear systems.IEEE Transac- tions on Control Systems Technology, 32(2):611–624, 2024

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:10.526900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:01.988941Z digest=sha256:cf38ba4d638fe245656c49f611939bdd4a88b6eded48b328979f2eb5afa266ce

Observation df5d43b5-7353-483c-987c-bf7d5115c6e3 · outbound

This paper cites Decentralized data-enabled predictive control for power system oscil- lation damping.IEEE Transactions on Control Systems Technology, 30(3):1065–1077, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Decentralized data-enabled predictive control for power system oscil- lation damping.IEEE Transactions on Control Systems Technology, 30(3):1065–1077, 2022

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:09.763215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.050374Z digest=sha256:cb122cbc29d452d7509ee641e8d8e28bd57c764aa15c6da37e83d9358ca1cd9d

Observation 195cc58e-2dc7-472b-8dc1-0560d3e96ee9 · outbound

This paper cites Data-driven continuous-set predictive current control for synchronous motor drives.IEEE Transactions on Power Electronics, 37(6):6637–6646, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Data-driven continuous-set predictive current control for synchronous motor drives.IEEE Transactions on Power Electronics, 37(6):6637–6646, 2022

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:09.300435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.109589Z digest=sha256:61f8320a559cb7f39e87089a13497f66e587bba5d92b3154534f4ef7d06bb484

Observation feb0ce78-7447-4d4e-8bfb-219c2acd686c · outbound

This paper cites Kerrigan, Paola Falugi, Marta Zagorowska, and Nilay Shah.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Kerrigan, Paola Falugi, Marta Zagorowska, and Nilay Shah

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:08.997497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.182328Z digest=sha256:202d1f0d703b8901c7d17229537100a7171e230aaaf71d033e3e3fedb338238c

Observation e2d9f2e5-36e4-48f1-ba9f-979b45d8c5ad · outbound

This paper cites A data-driven model predictive control for alleviating thermal overloads in the presence of possible false data.IEEE Transactions on Industry Applications, 57(2):1872–1881, 2021.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning A data-driven model predictive control for alleviating thermal overloads in the presence of possible false data.IEEE Transactions on Industry Applications, 57(2):1872–1881, 2021

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:08.640717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.276240Z digest=sha256:6a896605d795cbd7b5aa2624af8eca1796be55307c77d80b1cbf9ccf13a962b6

Observation dfa6a047-7141-4192-8ac0-8099c01e700e · outbound

This paper cites An outlier detection scheme for dynamical sequential datasets.Commu- nications in Statistics-Simulation and Computation, 48(5):1450–1502, 2019.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning An outlier detection scheme for dynamical sequential datasets.Commu- nications in Statistics-Simulation and Computation, 48(5):1450–1502, 2019

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:07.984976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.354545Z digest=sha256:6c46abf1760682e702a366b6fdb1652ce634744bbb7c43e03dff361e2d6c3f7e

Observation b360cfcd-49f6-4fa0-b224-944d0a4c12ea · outbound

This paper cites Sequential outlier criterion for sparsification of online adaptive filter- ing.IEEE Transactions on Neural Networks and Learning Systems, 29(11):5277–5291, 2018.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Sequential outlier criterion for sparsification of online adaptive filter- ing.IEEE Transactions on Neural Networks and Learning Systems, 29(11):5277–5291, 2018

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:07.782468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.422708Z digest=sha256:b4a77ba16dea69cedf9ffd833998eda0619b95cb1944aa7bd0add848d1d84aca

Observation c7efdb57-1a0b-4824-9387-807b613f79cb · outbound

This paper cites Robust data-enabled predictive control: Tractable formulations and performance guarantees.IEEE Transactions on Automatic Control, 68(5):3163–3170, 2023.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Robust data-enabled predictive control: Tractable formulations and performance guarantees.IEEE Transactions on Automatic Control, 68(5):3163–3170, 2023

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:07.596006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.479342Z digest=sha256:1fda269d32270a1059362651446bab17ecc9ff2552fd5a80565e1a49e37493a7

Observation e79957f4-bcd6-4213-a34d-36ffc0803222 · outbound

This paper cites On the equivalence of direct and indirect data-driven predictive control approaches.IEEE Control Systems Letters, 2024.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning On the equivalence of direct and indirect data-driven predictive control approaches.IEEE Control Systems Letters, 2024

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:07.387720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.546171Z digest=sha256:c50ff3f59c37bd573be862e98c3cb59e4b1ec6cec91b91d54e99991f7bd788d7

Observation 6826ab8a-4b6d-492b-ada8-352c931c5527 · outbound

This paper cites Data-driven predictive control with improved per- formance using segmented trajectories.IEEE Transactions on Control Systems Technology, 31(3):1355–1365, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Data-driven predictive control with improved per- formance using segmented trajectories.IEEE Transactions on Control Systems Technology, 31(3):1355–1365, 2022

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:07.214909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.614600Z digest=sha256:6b6953d533adaa5113627bdd1ec4d61953813963497df4fa52bbdd7aeb8159cc

Observation f0afbf1d-32cc-4ee7-b7a7-c035e2bd8449 · outbound

This paper cites Data-driven control based on the behavioral approach: From theory to applications in power systems.IEEE Control Systems Magazine, 43(5):28–68, 2023.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Data-driven control based on the behavioral approach: From theory to applications in power systems.IEEE Control Systems Magazine, 43(5):28–68, 2023

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:07.036099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.681347Z digest=sha256:f0507cec67f41cf5b68154164a22ee274a47039ba9f8ec8696cb5fbca383d9f5

Observation f47683ab-66d7-45ea-9cfb-3ed23ad7f61d · outbound

This paper cites On the relationship between data-enabled predictive control and subspace predictive control.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning On the relationship between data-enabled predictive control and subspace predictive control

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:06.876395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.757163Z digest=sha256:4d13ba1c208539bd213a1aa74cb81a90c1c8612448b1bdfa675453368871863d

Observation 1fd3f74c-2e1f-438b-84be-a7a393177ae4 · outbound

This paper cites Physics-augmented data-enabled predictive control for eco-driving of mixed traffic considering diverse human behaviors.IEEE Transactions on Control Systems Technology, 2024.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Physics-augmented data-enabled predictive control for eco-driving of mixed traffic considering diverse human behaviors.IEEE Transactions on Control Systems Technology, 2024

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:06.719643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.834566Z digest=sha256:307596da101f9d13a527af0f2baeac183eab42ad753559eb0959cac3a515b299

Observation a816f426-32dd-44df-b91d-ce5786ceedc6 · outbound

This paper cites Cloud- based computational data-enabled predictive control.IEEE Internet of Things Journal, 9(24):24949–24962, 2022.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Cloud- based computational data-enabled predictive control.IEEE Internet of Things Journal, 9(24):24949–24962, 2022

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:06.532553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:02.921364Z digest=sha256:1dcc94a57dc7342a0bf6c6495a10ffee83415784e750f4dd577f200d33ee2419

Observation 7b0ffdaf-6553-4c43-9647-cbf01c1198be · outbound

This paper cites An extended kalman filter for data-enabled predictive control.IEEE Control Systems Letters, 4(4):994–999, 2020.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning An extended kalman filter for data-enabled predictive control.IEEE Control Systems Letters, 4(4):994–999, 2020

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:06.362142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.008958Z digest=sha256:8dd1950b45f9342aacb606633704b9330009469b51b87965bf522f310d6fb219

Observation e227bc2b-95a1-4307-bbce-9d5e979e425f · outbound

This paper cites Subspace predictive control of flexible structures actuated by piezoelectric elements.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Subspace predictive control of flexible structures actuated by piezoelectric elements

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:06.162838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.065123Z digest=sha256:3a1164df478dbe45e86af4d35c8ecfac02868ec4a25da51c0c56848c6ab31261

Observation 66cecc5d-eaab-4262-b41f-f8898de6d823 · outbound

This paper cites Decentralized data-enabled predictive control for power system oscil- lation damping.IEEE Transactions on Control Systems Technology, 30(3):1065–1077, 2021.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Decentralized data-enabled predictive control for power system oscil- lation damping.IEEE Transactions on Control Systems Technology, 30(3):1065–1077, 2021

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:05.946095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.147438Z digest=sha256:dc262df208b59ecf97d797e6adad1beeae7da104e980fcd3c958db8d1688d247

Observation ebaa234d-e565-461e-a000-87a605e15b42 · outbound

This paper cites Harnessing uncertainty for a separation principle in direct data- driven predictive control.Automatica, 173:112070, 2025.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Harnessing uncertainty for a separation principle in direct data- driven predictive control.Automatica, 173:112070, 2025

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:05.780375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.259381Z digest=sha256:c7969a9c7f763ea012be38bd131ca546cc59d3ad38fd74449b89c27ec297cfa5

Observation ee8ce7a4-f2d1-4a21-8c90-85520092248b · outbound

This paper cites Offset–free data–driven predictive control.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Offset–free data–driven predictive control

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:05.614962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.329125Z digest=sha256:05384dd2c3e08bc312418803f61ec0d88444958e4ac68801676f7cad7274d08c

Observation a830ed79-35c8-4a41-bb67-365a11722863 · outbound

This paper cites Handbook of linear data-driven predictive control: Theory, implementation and design.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Handbook of linear data-driven predictive control: Theory, implementation and design

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:05.414425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.397780Z digest=sha256:e5fa157901971b8773fea5629b81ca576df5753f1c2b3120a1ae5c972b3136cd

Observation 04f51744-6ffe-4ac5-ad72-5865446d014c · outbound

This paper cites DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization

Reference 55

Resolution
verified exact
local_arxiv, observed 2026-08-07T12:24:03.855862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.488121Z digest=sha256:778051b273728c10326a2515fb184b8e3e93039217a9d3abee8f15cc828ba4bf

Observation a4440639-bce2-44bf-811e-48dbd33d29f9 · outbound

This paper cites Q- learning based linear quadratic regulator with balanced exploration and exploitation for unknown systems.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Q- learning based linear quadratic regulator with balanced exploration and exploitation for unknown systems

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:05.210287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.568475Z digest=sha256:4ca565adb5eff5cdf37398df264ecb5eb016c3422eea7ca219ffdba2a7c2636c

Observation 9e6d96f8-acd1-4af0-94e7-d9c1ff131f31 · outbound

This paper cites Reinforcement learning: An introduction.

Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Reinforcement learning: An introduction

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:24:05.028102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:24:03.669417Z digest=sha256:a68651bde8f9a03141b78cb592a13ad4c6c036ff4f75d1a247b445e518cc2107

Pith citing papers

No inbound Pith citation observations are available.