non-linear-systems

Course Project (ELEC 841 @ Queen's University)

LQR-LQG-Controller Design

ScaledRelativeGraphs.jl — Computable SRG-based stability certificates for engineering practice. Bridges theory and application with standards compliance, measured-data workflows, and visualization. Julia.

Extended State Space Model for JAX

PHY407 Computational Physics

Final Project for the winter term 2021/22 Scientific Computing lecture at the Technical University of Berlin

Assignment codes for Introduction to Numerical Analysis (2020, FGV-EMAp).

Comprehensive C++ implementations of Numerical Methods with detailed mathematical theory

Code Samples and Exercises during Numerical Analysis Class

EN: Identification and MPC control of reverse pendulum on cart system. University project for the exam 'Identification and Control Process'. ---- IT: Identificazione e controllo di un sistema pendolo inverso su carrello. Progetto universitario per l'esame "Identificazione e Controllo dei Processi".

This project simulates an experiment using Adaptive Random Fourier Features Kernel Least Mean Squares (ARFF-KLMS) to approximate non-linear functions. The algorithm adapts kernel bandwidth online, enhancing tracking and convergence in non-stationary environments. The experiment calculates and plots MSE over iterations for performance evaluation.

Material from the course of Nonlinear Systems and Robustness at ENSEM - Université de Lorraine.

Projeto efetuado para a disciplina de Cálculo Numérico (MS211 - Unicamp - 2019), que implementa a solução de um sistema não linear. Utiliza o método de Newton discreto para cálculo do sistema não linear, e o método de Gauss-Jacobi para cálculo de sistemas lineares.

BSU labs on solving non-linear equations and non-linear systems

Lightweight Newton-Raphson Solver with Gauss Elimination and Partial Pivoting

Numerical methods toolkit for solving linear systems (Gauss Elimination, Gauss-Jordan, LU/Doolittle/Crout/Cholesky, Jacobi, Gauss-Seidel) and finding roots of nonlinear equations (Bisection, False Position, Fixed-Point, Newton-Raphson, Secant), with step-by-step solutions and function plotting.

This project demonstrates a simulation of an experiment using Random Fourier Features (RFF) to approximate a non-linear function. The experiment is designed to be repeated multiple times, and the mean squared error (MSE) is calculated and plotted over iterations to evaluate the performance of the model.

Basic set of codes for solving linear and non-linear ordinary differential equations.