Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
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Updated
Jun 21, 2022 - Python
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
iterative Linear Quadratic Regulator with support for constraints on input and state variables via barrier functions—Numba-accelerated.
This repository has the code for the nonlinear model predictive controller for target tracking problems with the use of Casadi framework and Matlab simulation environment. 🏎️
A path following differential drive robot controlled using a PID controller and Model Predictive Controller (MPC)
Z. Sun, Q. Wang, J. Pan and Y. Xia, "Data-Driven MPC for Linear Systems using Reinforcement Learning," 2021 China Automation Congress (CAC), Beijing, China, 2021, pp. 394-399, doi: 10.1109/CAC53003.2021.9728233.
This study explores using RL for CSTR control, assessing effectiveness vs. traditional controllers (PID, MPC). RL learns optimal behavior to maximize rewards, outperforming NMPC with exploration and lower computational load.
Automated Driving block week project
OPSR 2025 Project
This repo contains all the codes of my control systems simulations
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