Suchergebnisse - "Data-driven control"

Online Learning of Stabilizing Controllers Using Noisy Input-Output Data and Prior Knowledge

Autoren: Niknejad, Nariman Adib Yaghmaie, Farnaz Modares, Hamidreza

Quelle: IEEE Open Journal of Control Systems. 4:156-171

Schlagwörter: Noise measurement, Data models, System identification, Symmetric matrices, Vectors, Stability criteria, Technological innovation, Mathematical models, Behavior theory, data-driven control, linear matrix inequalities, robust control, uncertain systems

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-216913
https://doi.org/10.1109/OJCSYS.2025.3570578

K-SMPC: Koopman Operator-Based Stochastic Model Predictive Control for Enhanced Lateral Control of Autonomous Vehicles

Autoren: Kim, Jin Sung Quan, Yingshuai Chung, Chung Choo et al.

Quelle: IEEE Access. 13:13944-13958

Schlagwörter: Approximation error, data-driven control, Computational modeling, Koopman operator, predictive control, Roads, Vehicle dynamics, Dynamics, Uncertainty, stochastic model, Autonomous vehicles, Nonlinear dynamical systems, Tires

Dateibeschreibung: electronic

Zugangs-URL: https://research.chalmers.se/publication/545077
https://research.chalmers.se/publication/545074
https://research.chalmers.se/publication/545084
https://research.chalmers.se/publication/545084/file/545084_Fulltext.pdf

Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

Autoren: Shahrizal Saat Mohd Ashraf Ahmad Mohd Riduwan Ghazali

Quelle: International Journal of Cognitive Computing in Engineering, Vol 6, Iss, Pp 74-99 (2025)

Schlagwörter: Data-driven control, Electronic computers. Computer science, Science, Nonlinear control system, 0202 electrical engineering, electronic engineering, information engineering, Safe experimentation dynamics algorithm, Brain emotional learning-based intelligent controller, 02 engineering and technology, QA75.5-76.95, MIMO system

Zugangs-URL: https://doaj.org/article/f289859cf2cb494c8d5c9f550a8cb411

An adaptive direct data-driven controller for nonlinear system reference tracking

Autoren: Luka Mandić Đula Nađ Nikola Mišković

Quelle: ISA Transactions: The Journal of Automation

Schlagwörter: Direct data-driven control, TECHNICAL SCIENCES. Electrical Engineering. Automation and Robotics, Dynamic positioning, Adaptive control Direct data-driven control Dynamic positioning Nonlinear systems Unmanned surface vehicle (USV), Nonlinear systems, Adaptive control, TEHNIČKE ZNANOSTI. Elektrotehnika. Automatizacija i robotika, Unmanned surface vehicle (USV), Adaptive control, Direct data-driven control, Dynamic positioning, Nonlinear systems, Unmanned surface vehicle (USV)

Dateibeschreibung: application/pdf

Zugangs-URL: https://urn.nsk.hr/urn:nbn:hr:168:053763
https://repozitorij.fer.unizg.hr/islandora/object/fer:13445
https://repozitorij.fer.unizg.hr/islandora/object/fer:13445/datastream/FILE0

Inverse supervised learning of controller tuning rules

Autoren: Lakshminarayanan, Braghadeesh Dettú, Federico Rojas, Cristian R. et al.

Quelle: Automatica. 178

Schlagwörter: Data-driven control, Inverse supervised learning, Meta learning, Neural networks, Sequence model

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-363415
https://doi.org/10.1016/j.automatica.2025.112356

Event-Triggered Data-Driven Predictive Control for Multirate Systems: Theoretic Analysis and Experimental Results

Autoren: Yi Yang Dawei Shi Hao Yu et al.

Quelle: IEEE/ASME Transactions on Mechatronics. 30:2450-2460

Schlagwörter: Optimization, Data-driven control, Noise measurement, Multirate systems, Trajectory, Linear systems, Sampled-data systems, Predictive control, Event-triggered control, Noise, Mechatronics

Data-Driven Control Design and Input Allocation for Strongly Redundant LPV Systems

Autoren: Faleschini, Michelangelo Cristofaro, Andrea

Quelle: 2025 33rd Mediterranean Conference on Control and Automation (MED). :322-327

Schlagwörter: Data-driven control, Input allocation

3HANDS Dataset: Learning from Humans for Generating Naturalistic Handovers with Supernumerary Robotic Limbs

Autoren: Artin Saberpour Abadian Yi-Chi Liao Ata Otaran et al.

Weitere Verfasser: Artin Saberpour Abadian Yi-Chi Liao Ata Otaran et al.

Quelle: CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

Schlagwörter: FOS: Computer and information sciences, I.2.10, Computer Vision and Pattern Recognition (cs.CV), I.3.7, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, I.2.9, supernumerary robotic limb, third arm, Human-Computer Interaction (cs.HC), H.5.2, Computer Science - Robotics, motion synthesis, dataset, generative model, Robotics (cs.RO), data-driven control in robotics, handover, wearable robotic arm

Dateibeschreibung: application/application/pdf

Zugangs-URL: http://arxiv.org/abs/2503.04635
http://hdl.handle.net/20.500.11850/738519

Neural motion planning in dynamic environments

Autoren: Wullt, Bernhard Mattsson, Per Schön, Thomas B., Professor et al.

Quelle: IFAC-PapersOnLine. 56(2):10126-10131

Schlagwörter: Data-driven control, Learning for control, Robots manipulators, Motion planning, Imitation learning

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-518375
https://doi.org/10.1016/j.ifacol.2023.10.885

Data-Driven Stabilization: A Robust Control Approach with Linear Matrix Inequalities

Autoren: Chandar Kumar Dur Muhammad Soomro Najeeb Ur Rehman Malik

Quelle: Sir Syed University Research Journal of Engineering and Technology, Vol 15, Iss 1 (2025)

Schlagwörter: TK7885-7895, Computer engineering. Computer hardware, Electronic computers. Computer science, nonlinear control system, T1-995, QA75.5-76.95, linear matrix inequalities, Control design, data-driven control, robust control, Technology (General), learning systems

Zugangs-URL: https://doaj.org/article/40b6fe05c123420f991b874cbd99a6a6

Data-Driven Mode Detection and Stabilization of Unknown Switched Linear Systems

Autoren: Jaap Eising Shenyu Liu Sonia Martínez et al.

Quelle: IEEE Transactions on Automatic Control, 70 (6)

Schlagwörter: Optimization and Control (math.OC), FOS: Mathematics, Data-driven control, linear systems, switched systems, Mathematics - Optimization and Control

Zugangs-URL: http://arxiv.org/abs/2303.11489
http://hdl.handle.net/20.500.11850/739411

On Data-Driven Stochastic Output-Feedback Predictive Control

Autoren: Guanru Pan Ruchuan Ou Timm Faulwasser

Quelle: IEEE Transactions on Automatic Control. 70:2948-2962

Schlagwörter: 0209 industrial biotechnology, Optimization and Control (math.OC), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 02 engineering and technology, Systems and Control (eess.SY), Data-driven control | model predictive control | output feedback | recursive feasibility | stochastic MPC | Willems' fundamental lemma | Witsenhausen, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control

Zugangs-URL: http://arxiv.org/abs/2211.17074

Necessary and Sufficient Conditions for Data-Driven Model Reference Control

Autoren: Jiwei Wang Simone Baldi Henk J. van Waarde

Quelle: IEEE Transactions on Automatic Control. 70:2659-2666

Schlagwörter: model reference control, quadratic matrix inequalities, Optimization and Control (math.OC), Data informativity, FOS: Mathematics, Mathematics - Optimization and Control, data-driven control

Zugangs-URL: http://arxiv.org/abs/2310.11159

Scenario-Optimization-Based Velocity Planning of Autonomous Vehicles for Interacting With Pedestrians

Autoren: Bence Jekl Zvonimir Dabčević Balázs Németh et al.

Quelle: IEEE Transactions on Intelligent Transportation Systems. 26:5382-5395

Schlagwörter: computational modeling, pedestrian modeling, real-time systems, scenario approach, vehicle dynamics, safety data models, pedestrians planning, velocity planning, autonomous vehicles, predictive models, data-driven control, adaptation models

Finding Approximate Correlated Equilibrium for Decentralized Control

Autoren: Rahul Misra Rafał Wiśniewski Carsten S. Kallesøe

Quelle: Misra, R, Wiśniewski, R & Kallesøe, C S 2025, 'Finding Approximate Correlated Equilibrium for Decentralized Control', IEEE Control Systems Letters, vol. 9, 11015923, pp. 414-419. https://doi.org/10.1109/LCSYS.2025.3573857

Schlagwörter: Decentralised Control, game theory, Decentralized control, Game Theory, Reinforcement Learning (RL), water distribution network, Stochastic Games, Data driven control, Blackwell's Approachability Theorem, Convergence, Correlated Equilibrium, Game theory, data driven control

Dateibeschreibung: application/pdf

Zugangs-URL: https://vbn.aau.dk/da/publications/ac485ef5-d7c1-4173-becc-9698011c4651
https://doi.org/10.1109/LCSYS.2025.3573857
http://www.scopus.com/inward/record.url?scp=105006933682&partnerID=8YFLogxK
https://vbn.aau.dk/ws/files/782121823/Accepted_Author_Manuscript.pdf

Intelligent power control using deep neural networks and regularized learning for shipboard microgrid

Autoren: Wenhua Deng Kaixia Lu Xinxin Li et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Schlagwörter: Shipboard microgrid, Data-driven control, Hybrid energy storage unit, Non-integer extended state observer (NIESO), Regularized actor-critic (RAC), Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/914f5b8580d34282b994ec379cdf5b5d

Data-Driven Control Design for Complex Systems: Theory, Challenges, and Novel Applications

Autoren: Chandar Kumar Muhammad Sabih Shubash Kumar et al.

Quelle: Sukkur IBA Journal of Computing and Mathematical Sciences, Vol 8, Iss 1 (2025)

Schlagwörter: TK7885-7895, Computer engineering. Computer hardware, classification, model-based control, Electronic computers. Computer science, QA1-939, QA75.5-76.95, optimization, data-driven control, Mathematics

Zugangs-URL: https://doaj.org/article/be13e9f2aea94e9f9ca63317191bca28

Online Constraint Tightening in Stochastic Model Predictive Control: A Regression Approach

Autoren: Alexandre Capone Tim Brüdigam Sandra Hirche

Quelle: IEEE Transactions on Automatic Control

Schlagwörter: coman, Stochastic processes, Uncertainty, Symbols, Optimal control, Computational modeling, Closed loop systems, Autonomous systems,data-driven control, machine learning, reinforcement learning, statistical learning, stochastic processes, uncertain systems, networked control system, scheduling design, event-triggered control, wireless communication, FOS: Computer and information sciences, Computer Science - Machine Learning, Statistics - Machine Learning, FOS: Electrical engineering, electronic engineering, information engineering, Machine Learning (stat.ML), Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, ddc, Machine Learning (cs.LG)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2310.02942
https://mediatum.ub.tum.de/1754978

Data‐Driven Adaptive Cooperative Output Regulation for Completely Unknown Linear Multi‐Agent Systems Based on Finite Length Data: Data-driven adaptive cooperative output regulation for completely unknown linear multi-agent systems based on finite length data

Autoren: Hong Chen Dong Liang Chaoli Wang et al.

Quelle: International Journal of Robust and Nonlinear Control. 35:2910-2919

Schlagwörter: linear discrete-time dynamics, Discrete-time control/observation systems, Adaptive control/observation systems, Linear systems in control theory, Multi-agent systems, Control/observation systems with incomplete information, cooperative output regulation, data-driven control

Dateibeschreibung: application/xml

Tractable Data-Driven Model Predictive Control Using One-Step Neural Networks Predictors

Autoren: Menegatti D. Giuseppi A. Pietrabissa A.

Quelle: IEEE Transactions on Automation Science and Engineering. 22:6740-6751

Schlagwörter: data-driven control, deep neural networks, mixed-integer convex programming, Model predictive control

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11573/1746636
https://doi.org/10.1109/TASE.2024.3453668