Results 181 to 190 of about 26,525,584 (210)

Event-driven model-free control in motion control with comparisons

IMA Journal of Mathematical Control and Information, 2016
The event-driven model-free control is proposed in this article, which deals with the ‘trade-off’ between computational cost and system performance. Model-free controllers demand low computational resources and have high robustness, which is especially suitable for embedded systems with complex dynamics and/or affected by disturbances.
Wang, Jing, Mounier, Hugues, Niculescu, Silviu-Iulian, Geamanu, Marcel-Stefan, Cela, Arben   +4 more
openaire   +2 more sources

Design of Model Free Adaptive Controller for PMSM Speed Control

2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019
In order to gain favorable control performance of permanent magnet synchronous motor (PMSM) drive system in the presence of structural perturbation and load disturbance, model free adaptive control (MFAC) method is introduced in the design of speed controller, since it only relies on the input and the output measurement data of the controlled plant ...
Ye Zhao, Wei Zhang, Xinbing Wu
openaire   +1 more source

Modifications of Model Free Control to FOTD Plants

2018
Model free control (MFC) represents one of possible alternatives to traditional approaches as PID control, disturbance observer based control (DOBC), internal model control (IMC), etc. As one of its central features one could mention use of finite-impulse-response (FIR) filters in input disturbance reconstruction.
Mikulás Huba, Tomás Huba
openaire   +2 more sources

Hybrid Model-Free and Model-Free Adaptive Fuzzy Controllers

2021
Radu-Emil Precup, Raul-Cristian Roman, Ali Safaei   +2 more
openaire   +1 more source

Model-Free Adaptive Controllers

2021
Radu-Emil Precup, Raul-Cristian Roman, Ali Safaei   +2 more
openaire   +1 more source

Model-Free Optimal Control: A Critical Analysis

2017
In this note, we present a critical analysis of machine learning techniques for applications involving optimal (feedback) control. Specifically, we will focus on the question of using reinforcement learning and other similar techniques in providing provably stable optimal controllers.
openaire   +2 more sources

Model-Free Control of the PVTOL

2024 International Conference on Control, Automation and Diagnosis (ICCAD)
Eduardo Tzitzihua García, Anai Camacho Luna, David Lara Alabazares, Abdelhamid Rabhi, Jérôme Bosche   +4 more
openaire   +2 more sources

Model Free Adaptive Control

2013
Zhongsheng Hou, Shangtai Jin
openaire   +1 more source

Comparison of wood pyrolysis kinetic data derived from thermogravimetric experiments by model-fitting and model-free methods

Energy Conversion and Management, 2020
Dieter Stapf, Uwe Riedel, Marco Tomasi Morgano   +2 more
exaly  

Model-free voltage control of active distribution system with PVs using surrogate model-based deep reinforcement learning

Applied Energy, 2022
Nanpeng Yu, Fei Ding, Zhe Chen
exaly