WangXiaoMingo/TensorDL-MPC
DL-MPC(deep learning model predictive control) is a software toolkit developed based on the Python and TensorFlow frameworks, designed to enhance the performance of traditional Model Predictive Control (MPC) through deep learning technology. This toolkit provides core functionalities such as model training, simulation, parameter optimization.
TensorDL-MPC helps operations engineers and process controllers enhance the performance of industrial control systems using deep learning. You provide historical operational data, and it trains a predictive model to output optimized control strategies for systems like chemical reactors or manufacturing lines. This results in improved accuracy, efficiency, and product quality in various industrial automation and intelligent manufacturing scenarios.
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Use this if you need to precisely control complex, high-dimensional, or nonlinear industrial processes and want to leverage deep learning to improve prediction and optimization.
Not ideal if your control problems are simple and linear, or if you prefer traditional control methods without deep learning integration.
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40
Forks
3
Language
Python
License
AGPL-3.0
Category
Last pushed
Mar 31, 2025
Commits (30d)
0
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