:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Mohammadi, Parham
Format:	Preprint
Published:	2025
Subjects:	Systems and Control
Online Access:	https://arxiv.org/abs/2502.12571
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Single-Shot Learning of Multirotor Controller Gains: A Data-Driven Approach with Experimental Validation
by: Mirtaba, Mohammad, et al.
Published: (2024)

Design and Implementation of DC-DC Buck Converter based on Deep Neural Network Sliding Mode Control
by: Zhiwei, Liu, et al.
Published: (2024)

A Neural Network Approach to a Modified Quadratic Boost Multiport Resonant Converter for Electric Vehicle Chargers
by: Rajeswari, V., et al.
Published: (2025)

Deep Reinforcement Learning-Aided Frequency Control of LCC-S Resonant Converters for Wireless Power Transfer Systems
by: Safari, Reza, et al.
Published: (2025)

Model-free Dynamic Mode Adaptive Control using Matrix RLS
by: Oveissi, Parham, et al.
Published: (2025)

Model-Free Dynamic Mode Adaptive Control for Data-Driven Control Synthesis
by: Oveissi, Parham, et al.
Published: (2026)

Analytic Design of Flat-Wire Inductors for High-Current and Compact DC-DC Converters
by: Mohammadi, Sajjad, et al.
Published: (2024)

A Novel Topology Recovery Method for Low Voltage Distribution Networks
by: Mohammadi, Sina, et al.
Published: (2025)

Decentralized Small Gain and Phase Stability Conditions for Grid-Forming Converters: Limitations and Extensions
by: Cifelli, Diego, et al.
Published: (2025)

Comprehensive Analysis and Experimental Design of High-Gain DC-DC Boost Converter Topologies
by: Adepoju, Webster, et al.
Published: (2024)

Low-frequency Resonances in Grid-Forming Converters: Causes and Damping Control
by: Zhao, Fangzhou, et al.
Published: (2024)

Deep Q-Learning-Based Gain Scheduling for Nonlinear Quadcopter Dynamics
by: Rastgoftar, Hossein, et al.
Published: (2026)

A Pipelined Memristive Neural Network Analog-to-Digital Converter
by: Danial, Loai, et al.
Published: (2024)

Towards Reliable Neural Optimizers: A Permutation Equivariant Neural Approximation for Information Processing Applications
by: Li, Meiyi, et al.
Published: (2024)

Modelling and Control of a Buck Converter Using State-Space Averaging and Classical Feedback Techniques
by: Nwachukwu, Sampson E.
Published: (2025)

Gain-Only Neural Operators for PDE Backstepping
by: Vazquez, Rafael, et al.
Published: (2024)

High-Gain Voltage-Multiplier Coupled Quadratic Boost Converter: A New Design for Small Scale PV Integration
by: Sali, Safa Mohammed, et al.
Published: (2025)

Hybrid Machine Learning Approach for Cyberattack Mitigation of Parallel Converters in a DC Microgrid
by: Souri, Naser, et al.
Published: (2024)

Connected C-Core Hybrid SRMs for EV Applications
by: Davarpanah, Gholamreza, et al.
Published: (2025)

A Power Electronic Converter Control Framework Based on Graph Neural Networks -- An Early Proof-of-Concept
by: Jakobeit, Darius, et al.
Published: (2026)

Model-Based Adaptive Control of Modular Multilevel Converters
by: Tebaldi, Davide, et al.
Published: (2024)

Deep Neural Network based Optimal Control of Greenhouses
by: Sathyanarayanan, Kiran Kumar, et al.
Published: (2023)

A Grid-Forming HVDC Series Tapping Converter Using Extended Techniques of Flex-LCC
by: Sun, Qianhao, et al.
Published: (2025)

Towards Reliable Neural Optimizers: Permutation-Equivariant Neural Approximation in Dynamic Data Driven Applications Systems
by: Li, Meiyi, et al.
Published: (2025)

Deep Reinforcement Learning-Based Control Strategy with Direct Gate Control for Buck Converters
by: Katayama, Noboru
Published: (2025)

Field Free Novel Architecture for Spintronic Flash Analog to Digital Converter
by: Francis, Abin, et al.
Published: (2026)

Physics-Informed Neural Network-Based Control for Grid-Forming Converter's Stability Under Overload Conditions
by: Kumar, Abhay, et al.
Published: (2025)

Prescribed-Performance-Aware Hybrid-Gain-Based Robust Controller
by: Shivam, Amit, et al.
Published: (2026)

A Novel Tunable Controller for Grid Forming Converters towards Critical Services Application
by: Tripathy, Yangyadatta, et al.
Published: (2025)

Multi-Task Lifelong Reinforcement Learning for Wireless Sensor Networks
by: Firouzjaei, Hossein Mohammadi, et al.
Published: (2025)

Deep Neural Network NMPC for Computationally Tractable Optimal Power Management of Hybrid Electric Vehicle
by: Park, Suyong, et al.
Published: (2024)

A Novel Radial-Flux IPM Eddy-Current Coupler for Wind Generator Applications
by: Mohammadi, Sajjad, et al.
Published: (2024)

Contracting Neural Networks: Sharp LMI Conditions with Applications to Integral Control and Deep Learning
by: Gokhale, Anand, et al.
Published: (2026)

Proximal Policy Optimization-Based Reinforcement Learning Approach for DC-DC Boost Converter Control: A Comparative Evaluation Against Traditional Control Techniques
by: Saha, Utsab, et al.
Published: (2023)

Collaborative Spacecraft Servicing under Partial Feedback using Lyapunov-based Deep Neural Networks
by: Nino, Cristian F., et al.
Published: (2025)

Dual-Port Grid-Forming Interconnecting Power Converters in Hybrid AC/DC Grids
by: Arévalo-Soler, Josep, et al.
Published: (2024)

A Deep Neural Network-based Frequency Predictor for Frequency-Constrained Optimal Power Flow
by: Jiang, Fan, et al.
Published: (2025)

Robust and Gain-Scheduling ${\cal H}_2$ Control Techniques for LFT Uncertain and Parameter-Dependent Systems
by: Wu, Fen
Published: (2026)

Variable Dead-Time Based Novel Soft-Start Method for Dual Active Bridge Converters
by: Wijesooriya, Sachith, et al.
Published: (2026)

Gain Scheduling with a Neural Operator for a Transport PDE with Nonlinear Recirculation
by: Lamarque, Maxence, et al.
Published: (2024)