LEARNING
Neural Network Tuning of FSMPC for Drives
Juana M. Martínez-Heredia, José L. Mora
- Year
- 2026
- Access
- Open access
Abstract
This preprint presents a neural network tuner for the finite state model predictive control of an induction motor. The tuner deals with the parameters of the controllers in the speed loop and in the stator current loop. The results are assessed using a five phase machine in an experimental setup. Data for the neural network training is obtained from the experiments using step tests.
Keywords
eess.SY
Related papers
LEARNING
Open access📊 1 cites
Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers
Keyi Shen, Glen Chou
2026
LEARNING
📊 0 cites
Artificial Intelligence enhanced smart welding islands: Foundation models revolutionizing manufacturing
Xiwei Wu, Wei Wu, Qiqi Chen +6 more
Robotics and Computer-Integrated Manufacturing · 2026
LEARNING
📊 0 cites
A deep reinforcement learning and a dynamic graph neural network-based scheduling agent to control a multi-task robot
Hedi Boukamcha, Anas Neumann, Monia Rekik +3 more
Robotics and Computer-Integrated Manufacturing · 2026
LEARNING
📊 0 cites
LLM Agent-driven Automated DFA Assessment with Fine-tuning and AAS-based RAG
Jiaxin Liu, Xiaofeng Zhou, Suyang Yu +5 more
Robotics and Computer-Integrated Manufacturing · 2026