Results 41 to 50 of about 2,883,845 (315)

Data-Driven Control Algorithm for Snake Manipulator

Applied Sciences, 2021
In some environments where manual work cannot be carried out, snake manipulators are instead used to improve the level of automatic work and ensure personal safety. However, the structure of the snake manipulator is diverse, which renders it difficult to
Kai Hu, Lang Tian, Chenghang Weng, Liguo Weng, Qiang Zang, Min Xia, Guodong Qin   +6 more
doaj   +1 more source

Data-driven distributed control: Virtual reference feedback tuning in dynamic networks [PDF]

, 2021
In this paper, the problem of synthesizing a distributed controller from data is considered, with the objective to optimize a model-reference control criterion.
Van Den Hof, Paul M.J., Steentjes, Tom R.V., Lazar, Mircea, Van Den Hof, Paul M.J.; id_orcid   +3 more
core   +1 more source

Data-driven optimal prediction with control [PDF]

Communications in Nonlinear Science and Numerical Simulation
This study presents the extension of the data-driven optimal prediction approach to the dynamical system with control. The optimal prediction is used to analyze dynamical systems in which the states consist of resolved and unresolved variables. The latter variables can not be measured explicitly. They may have smaller amplitudes and affect the resolved
Aleksandr Katrutsa, Ivan V. Oseledets, Sergey V. Utyuzhnikov   +2 more
openaire   +2 more sources

Data-Driven LQR Control Design [PDF]

IEEE Control Systems Letters, 2019
This paper presents a data-driven solution to the discrete-time infinite horizon LQR problem. The state feedback gain is computed directly from a batch of input and state data collected from the plant. Simulation examples illustrate the convergence of the proposed solution to the optimal LQR gain as the number of Markov parameters tends to infinity ...
Gustavo R. Goncalves da Silva, Alexandre S. Bazanella, Charles Lorenzini, Lucíola Campestrini   +3 more
openaire   +2 more sources

Data‐driven safe gain‐scheduling control

Asian Journal of Control, 2023
AbstractData‐based safe gain‐scheduling controllers are presented for discrete‐time linear parameter‐varying systems (LPV) with polytopic models. First, ‐contractivity conditions are provided under which the safety and stability of the LPV systems are unified through Minkowski functions of the safe sets. Then, a data‐based representation of the closed‐
Amir Modares, Nasser Sadati, Hamidreza Modares   +2 more
openaire   +2 more sources

On the Impact of Regularization in Data-Driven Predictive Control

2023 62nd IEEE Conference on Decision and Control (CDC), 2023
Model predictive control (MPC) is a control strategy widely used in industrial applications. However, its implementation typically requires a mathematical model of the system being controlled, which can be a time-consuming and expensive task. Data-driven predictive control (DDPC) methods offer an alternative approach that does not require an explicit ...
Breschi, Valentina, Chiuso, Alessandro, Fabris, Marco, Formentin, Simone   +3 more
openaire   +2 more sources

Generalized Data–Driven Predictive Control: Merging Subspace and Hankel Predictors

Mathematics, 2023
Data–driven predictive control (DPC) is becoming an attractive alternative to model predictive control as it requires less system knowledge for implementation and reliable data is increasingly available in smart engineering systems.
M. Lazar, P. C. N. Verheijen
doaj   +1 more source

Informativity conditions for data-driven control based on input-state data and polyhedral cross-covariance noise bounds [PDF]

, 2022
Modeling and control of dynamical systems rely on measured data, which contains information about the system. Finite data measurements typically lead to a set of system models that are unfalsified, i.e., that explain the data.
Van den Hof, Paul M.J., Steentjes, Tom R.V., Lazar, Mircea, Van den Hof, Paul M.J.; id_orcid   +3 more
core   +1 more source

Contamination Detection From Highly Cluttered Waste Scenes Using Computer Vision

IEEE Access
As the global production of waste continues to rise, there is a growing demand for more effective waste management strategies to handle this expanding problem.
Dishant Mewada, Cathaoir Agnew, Eoin M. Grua, Ciaran Eising, Patrick Denny, Mark Heffernan, Ken Tierney, Pepijn van de Ven, Anthony Scanlan   +8 more
doaj   +1 more source

Tube-Based Zonotopic Data-Driven Predictive Control

, 2023
We present a novel tube-based data-driven predictive control method for linear systems affected by a bounded addictive disturbance. Our method leverages recent results in the reachability analysis of unknown linear systems to formulate and solve a robust
Proutiere, Alexandre,, Russo, Alessio,
core   +1 more source