mirror of
https://github.com/WallabyLester/RBF-aPID-Controller.git
synced 2026-05-17 23:36:16 +08:00
Andru Liu
26 lines
1.0 KiB
Markdown
26 lines
1.0 KiB
Markdown
# RBF-aPID-Controller
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RBF Neural Net Adaptive PID Controller
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Implementations of a radial basis function (RBF) neural network adaptive PID controller. Uses
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neural net and error information from PID control to adapt the control signal. Provides one
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adaptation value, using error, integral, and derivative.
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To adapt the PID gains themselves, network outputs must be made to 3 neurons. Example usage
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with simulated data can be found in [first_order_sim.py](first_order_sim.py)
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The method has been implemented in three ways:
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1. [TF_Implementation](/TF_Implementation/): Using TensorFlow to build and train the RBF Model.
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2. [NP_Implementation](/NP_Implementation/): Using Numpy to build and train the RBF Model.
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3. [CPP_Implementation](/CPP_Implementation/): Written in C++ (requiring `cmath`), for use on embedded systems.
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To build executable: `g++ RBF_aPID.cpp -o RBF_aPID.exe`\
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To run: `./RBF_aPID.exe`
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