isri-aist/DataDrivenMPC
Model predictive control based on data-driven model
This project helps robotics engineers and control systems designers implement model predictive control (MPC) for complex systems. It takes in operational data from a robot or system to learn its dynamics, then uses this learned model to predict future behavior and make optimal control decisions. The output is a robust control strategy that adapts to the system's real-world performance.
No commits in the last 6 months.
Use this if you need to control dynamic systems, especially robots, where precise mathematical models are difficult to obtain or change frequently, and you want to leverage operational data to improve control.
Not ideal if you have simple systems with well-defined analytical models, or if you are not working within a ROS environment.
Stars
29
Forks
3
Language
C++
License
BSD-2-Clause
Category
Last pushed
Aug 04, 2023
Commits (30d)
0
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