pyvrft: A Python package for the Virtual Reference Feedback Tuning, a direct data-driven control method

Boeira, Emerson Christ; Eckhard, Diego

doi:10.1016/j.softx.2019.100383

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…The above optimization problem can be solved by the quadratic programming (QP) method that searches for the best controller parameter θVRFT to minimize the J VRFT (θ) criterion. In this research, the solving algorithm was implemented in Python, adopted from the Pyvrft library [23]. The VRFT optimization problem is a mathematical equivalence to the conventional model-reference optimization problem described by Equations ( 3) and (4), as proven in [22].…”

Section: Adaptive Controller Designmentioning

confidence: 99%

Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning

et al. 2020

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Closed-loop control is desirable in direct energy deposition (DED) to stabilize the process and improve the fabrication quality. Most existing DED controllers require system identifications by experiments to obtain plant models or layer-dependent adaptive control rules, and such processes are cumbersome and time-consuming. This paper proposes a novel data-driven adaptive control strategy to adjust laser voltage with the melt pool size feedback. A multitasking controller architecture is developed to incorporate an autotuning unit that optimizes controller parameters based on the DED process data automatically. Experimental validations show improvements in the geometric accuracy and melt pool consistency of controlled samples. The main advantage of the proposed controller is that it can adapt to DED processes with different part shapes, materials, tool paths, and process parameters without tweaking. System identification is not required even when process conditions are changed, which reduces the controller implementation time and cost for end-users.

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Section: Adaptive Controller Designmentioning

confidence: 99%

Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning

et al. 2020

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“…In recent years, more novel ways ar explored to develop model predictive control, for example, the idea of data driven, mentioned above, is combined with model predictive control to yield a new control strategy-data driven model predictive control. In [14], data driven model predictive control is applied to design the classical PID for a deterministic continuous time system. For the case of switching controllers in some industries, data driven model predictive control is also benefit in regulating the switching rule [15].…”

Section: Introductionmentioning

confidence: 99%

Direct Data Driven Model Reference Control for Flight Simulation Table

Wang

Ramirez‐Mendoza

2022

IEEE Access

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We present a direct data driven model reference control framework for flight simulation table from both the theoretical analysis and engineering application. Sate of the art direct driven model reference control designs the unknown controller based on the input-output data and guarantees the actual model converge to the reference model, under a case of no any priori knowledge for the unknown plant. We improve this direct data driven model reference control strategy by considering its stability validation and synthesis analysis for nonlinear controller. The resulting direct data driven model reference control scheme can be implemented to ensure flight simulation table rotate accuracy, resulting in improved performance index. As the main technical contribution, we show that the proposed direct data driven model reference control framework also ensures closed loop stability and suitable extension for nonlinear controller.INDEX TERMS Model reference control, direct data driven, flight simulation table, synthesis analysis. RICARDO A. RAMIREZ-MENDOZA received the Ph.D. degree from INPG, France, in 1997. He is currently a Professor in mechatronicsmechanics and the Dean of Research with the School of Engineering and Science, Tecnologico de Monterrey. He is the coauthor of three books, more than 80 papers in top journals and more than 200 international conference papers and more than 1,000 citations. He has worked as an Expert consulting for different industries. He is also a Certified Reviewer for Regional Development Projects. His research interest includes applications of advanced control to automotive systems.

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“…During these two years, a new interesting subject about persistently of excitation is studied again in data driven control and model predictive control.Willem's fundamental lemma from [17] gives a data based parametrization of trajectories for one linear time invariant system. Based on this Willem's fundamental lemma, one parametrization of linear closed loop system is derived to pave a way to study important controller design problems [18].…”

Section: Introductionmentioning

confidence: 99%

Direct Data Driven Scheme for UAV Flight Control

2022

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Consider one special closed loop system structure with one unknown plant and two unknown controllers,i.e. feed froward controller and feedback controllers, our missions are to identify this plant and design these two controllers without any physical principles. Based on the measured input-output data sequence, direct data driven scheme is proposed to achieve these dual goals. For the case of parameterized plant and two parameterized controllers, two kinds of unknown parameter vectors are estimated from the data sequence, and the iterative idea is applied to identify them recursively until to be convergence. In addition, controller validation modular is added to testify whether the designed controllers are satisfied, being from the idea of model validation in system identification. Then theoretical analysis on direct data driven scheme can be implemented to guarantee UAV flight control structure work well, bringing the detailed UAV flight control performance. INDEX TERMSDirect data driven control. Controller validation. UAV flight control. Iterative idea.

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pyvrft: A Python package for the Virtual Reference Feedback Tuning, a direct data-driven control method

Cited by 7 publications

References 26 publications

Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning

Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning

Direct Data Driven Model Reference Control for Flight Simulation Table

Direct Data Driven Scheme for UAV Flight Control

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