Lyapunov-stable Neural Control for State and Output Feedback
[IROS 22'] Model-free Neural Lyapunov Control
Neuro-Fuzzy Control Assignments for ECE NTUA 9th Semester Course "Neuro-Fuzzy Control and Applications" (ECE1374)
Algorithms to investigate (through neural control) the representational relationships between univariate or multivariate in silico fMRI responses of multiple visual areas of the brain.
6DOF quadcopter simulator by Christian González Pérez, developed as a Final Degree Project (TFG) at the University of León.
Model Reference Neural Control (MRNC) implementation using Deep Learning for accurate trajectory tracking of a Differential-Drive Mobile Robot (DDMR).
A fast, smooth, algebraic alternative to Mish for TinyML and Edge AI. LiteMish uses only addition and multiplication, resulting in improved computational efficiency while preserving learning performance.
Robot air-hockey player (university project)
In this repository, a neural-network-PI (NN-PI) hybrid controller has been designed to maintain voltage stability when considering load changes in an islanded single-DG MG. A NN-based controller has also been designed for maximum power point tracking (MPPT) of PV panels. Conventional PI controllers have been designed for energy storage devices.
Hion (/ˈiː.ɒn/): Hamiltonian-Informed Optimal Neural Control.
In this repository, a neural-network-based controller has been designed to maintain voltage stability in an islanded single-DG microgrid (MG). A neural-network-based controller has also been designed for maximum power point tracking (MPPT) of PV panels. Conventional PI controllers have been designed for energy storage devices.
Official codebase for the paper "Blending Neural Control Density Functions for Stabilization and Safety" (ICML 2026)
Connectome-constrained simulation of the Drosophila heading circuit, with sparse feedback control, lesion experiments, and reproducible evaluation.
Scalar robust-control study comparing neural actions, clipping, model-based projection and linear feedback.
Simulation research on neural aircraft recovery, concurrent failures, bounded runtime assurance, and Z3 verification.
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