Neural Networks are good at curve fitting which makes them useful for inference +- noise. In control systems you need to do inference to predict feedback signa

Neural Networks are good at curve fitting which makes them useful for inference +- noise. In control systems you need to do inference to predict feedback signals +- noise. So you can use a neural network for that. Train it on input and feedback data from your samples. Your control system still needs to account for predictability, smooth behaviour etc so you have the rest of your machinery to handle that. This is not an end-to-end system though. Anyone know if there are end-to-end deep learning controllers with guarantees on the output space?