The design of neural networks (NNs) is presented for treating large, linear model predictive control (MPC) applications that are out reach with available quadratic programming (QP) solvers. First, we introduce a new feedforward network architecture enables practitioners to obtain offset-free closed-loop performance NNs. Second, discuss the data generation procedure sample state space relevant t...