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1. Model-Predictive-Control-Implementation-in-Python-1 Model-Predictive-Control-Implementation-in-Python-1 Public

   Here, we post the codes that implement the Model Predictive Controller (MPC) for linear systems.

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2. Model-Predictive-Control-for-Linear-Systems-in-Cpp-by-Using-Eigen-Library Model-Predictive-Control-for-Linear-Systems-in-Cpp-by-Using-Eigen-Library Public

   This repository contains C++ files that explain how to implement the Model Predictive Control (MPC) algorithm for linear systems in C++ by using the Eigen C++ matrix library.

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3. Subspace-Identification-State-Space-System-Identification-of-Dynamical-Systems-and-Time-Series- Subspace-Identification-State-Space-System-Identification-of-Dynamical-Systems-and-Time-Series- Public

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4. Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks Machine-Learning-of-Dynamical-Systems-using-Recurrent-Neural-Networks Public

   This project deals with learning to reproduce the input-output behavior of state-space models using recurrent neural networks and the Keras machine learning toolbox.

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5. Kalman-Filter-Implementation-in-Cpp-Using-Eigen-Library Kalman-Filter-Implementation-in-Cpp-Using-Eigen-Library Public

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6. Linear-Quadratic-Regulator-Optimal-Control-in-Cpp-From-Scratch-by-Using-Newton-Method Linear-Quadratic-Regulator-Optimal-Control-in-Cpp-From-Scratch-by-Using-Newton-Method Public

   We implemented a solution of the Linear Quadratic Regulator (LQR) Optimal Control problem in C++. We use the Newton method to solve the Riccati equation and to compute the solution.

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