Companion code for Uncertainty Modelling and Robust Observer Synthesis using the Koopman Operator
Model Predictive control is used in Industries across varied processes for ensuring control of target variables while manipulating inputs. We try to explore different paradigms of such control infrastructures to add stability and improve convergence on a multivariable system
Code for the paper "A Scalable Approach for Analysing Multi-Agent Systems with Heterogeneous Stochastic Packet Loss" by C. Hespe and H. Werner
Decentralized Tube-Based Model Predictive Controller. Master Thesis project 2024
Matlab code for quantum spin-1/2 networks. It provides code to analyse the geometry of such networks, and some basic quantum control and characterisation code.
A Julia package for the computation of hard, theoretically guaranteed bounds on the moments of jump-diffusion processes with polynomial data
nonlinear control system, non-linear system
sliding mode control and estimation methods for robotic systems
disturbance-rejection by MEC
Robust control of a hard disk drive servo system
This repository contains the file made for the Controllo dei Sistemi Incerti project and a Matlab Live Script that wants to help the newbies to approach the Robust Control with Matlab
Just Another Control Library - part of my capstone project
Code to compare log sensitivity and RIM robustness measures of energy landscape controllers
A Python implementation of a Direct Data-Driven Model Predictive Control (MPC) controller for Linear Time-Invariant (LTI) systems, based on the work of J. Berberich et al. presented in the paper "Data-Driven Model Predictive Control With Stability and Robustness Guarantees".
Code and data for differential sensitivity bounds for dynamic control used in "Robustness of Dynamic Quantum Control: Differential Sensitivity Bounds".
Design and integration of Guidance, Navigation and Control systems for autonomous robot swarms
Computationally tractable learning-based nonlinear tube MPC using difference of convex neural network dynamic approximation
This approach is used to solve robust safe navigation using control density function.
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