🚀 Execute commands and transfer files with your custom RPC server, enabling stealthy operations and bypassing common detection methods.

Build AI motion design for After Effects and frontend animations from chat with ExtendScript and live code previews

Optimal and Robust Control – a graduate course B(E)3M35ORR at CTU in Prague, Czechia

LQR state-feedback and reduced-order observer for aircraft landing flare control. Includes continuous and discrete (Simulink) implementations. Academic project at ITA.

Controlador LQR y Filtro de Kalman para péndulo invertido (GNC) mediante metodología Model-Based Design (MBD).

Two-body orbital propagator + Clohessy-Wiltshire LQR/LQI rendezvous controller, with Bayesian-optimized cost weights as the bridge from classical control toward learning-based control.

Digital Control is a Python-based engineering toolkit for studying, simulating, and designing discrete-time control systems through reproducible CLI workflows, structured inputs, and file-based outputs.

Python-first control systems toolkit for reproducible CLI workflows, plots, JSON outputs, and textbook-aligned analysis/design tools across classical and modern control.

Modular trajectory tracking controller for CARLA + ROS 2 — benchmarks LQR, MPC, Stanley, Pure Pursuit, and PD lateral controllers with 2D-calibrated PID longitudinal control.

现代控制理论主干学习线与配套数值实验，覆盖状态空间、稳定性、可控可观、观测器、最优控制、采样控制与鲁棒控制

时空联合规划al-ilqr求解器

6DOF fighter flight control system with LQR-based SAS and thrust vectoring. Demonstrates optimal state feedback, actuator allocation, and real-time FlightGear visualization.

Desktop-grade 2D rocket lander engineering simulator for PID and state-space control tuning

Safety-critical control for a tilt-rotor bicopter using High-Order Control Barrier Functions (HOCBF) and LQR, with guaranteed altitude constraint satisfaction in MATLAB/Simulink.

Full autopilot pipeline for a tilt bicopter: 6-DOF dynamics, LQR control, complementary-filter AHRS, and RRT path planning with obstacle avoidance.

Real-time LQR balance controller for an inverted pendulum on Arduino Mega 2560 — split angle/cart control at 200 Hz with quadrature encoder feedback.

HILO-MPC is a Python toolbox for easy, flexible and fast development of machine-learning-supported optimal control and estimation problems

Self-contained benchmark for vehicle path-tracking controllers (Stanley, Pure Pursuit, PID, LQR, MPC) with live simulation, quantitative evaluation, and visualization in Python.

For Learning Suspension control in vehicles,implemented a Closed-Loop Active Suspension Controller for a quarter-car model.

This repository contains CartPole simulator with its GUI, implemented controller (LQR) and generator of random desired position trace. It also contains files to train and test RNN predicting future states of a CartPole.