collection of extremum seeking control implementations

Extremum Seeking (ES) is a model-free optimization and control algorithm that can be used online or offline. This repo contains several plug and play types of ES along with simulation examples.

This repo corresponds to project titled as "Higher-order Lie bracket approximation and averaging of control-affine systems with application to extremum seeking."

Adaptive control-oriented meta-learning for nonlinear systems

Easily download and manage single-player game cheats for your convenience

Computer vision assisted tool to extract numerical data from plot images.

This is the official repository to PARODIS, the Matlab PAReto Optimal Model Predictive Control framework for DIstributed Systems.

PythonLinearNonLinearControl is a library implementing the linear and nonlinear control theories in python.

A generalized approach to find the K&M matrices, eigenvalues, and natural frequencies of a beam with n subdivisions

Modal Analysis using FEM with Python. Each program finds the frequencies and vibration shapes for a beam, air in an enclosed cavity and water sloshing.

The implementation of the beam models and the subsequent homogenized beam finite element (HBFEM) model correctly characterizes the transverse dynamics of real buildings if the structure fulfills sp…

Linear finite element code for 3D Euler-Bernoulli beam elements

Velocity-based finite element formulation for nonlinear dynamic analysis of beams

A finite element program for solving 3D-Structure comprising of Beams

A finite element method for beam-like structures.

Transverse Vibration Analysis of Euler-Bernoulli Beam

This repository uses ACAR methods, stochastic approximation and other methods of nonlinear and adaptive control systems

The reliable solution of nonlinear parameter estimation problems is an essential computational and mathematical problem in process systems engineering, both in on-line and off-line applications. Pa…

A dual-control effect preserving formulation for nonlinear output-feedback stochastic model predictive control with constraints

The Python codes, of the algorithms for linear and nonlinear systems, used in our paper``State estimation for control: an approach for output-feedback stochastic MPC''.

This repository contains the source code for “Unscented Kalman filter stochastic nonlinear model predictive control” (UKF-SNMPC).

Implementations of Control (PID, LQ, MPC, ...) and AI (fuzzy logic, Q-learner, SARSA, ...) algorithms

an simple model predictive control demo in matlab2018b

Experimental and analytical study of a vibratory system with multiple degrees of freedom (GL) - using MATLAB

Continuous control with deep reinforcement learning - Deep Deterministic Policy Gradient (DDPG) algorithm implemented in OpenAI Gym environments

MATLAB codes for the book (in Farsi) " Structural Dynamics and Vibration Control"

Observer-Based Repetitive Model Predictive Control in Active Vibration Suppression

A Parallel Optimization Toolkit for Nonlinear Model Predictive Control (NMPC)