Efficient Representation and Approximation of Model Predictive Control Laws via Deep Learning

We show that artificial neural networks with rectifier units as activation functions can exactly represent the piecewise affine function that results from the formulation of model predictive control (MPC) of linear time-invariant systems. The choice of deep neural networks is particularly interestin... View More