Parallel move blocking Model Predictive Control

This paper proposes the use of parallel computing architectures (multi-core, FPGA, GPU) to implement a parallel move blocking Model Predictive Control (MPC) algorithm where multiple, but smaller optimization problems are solved simultaneously. Since these problems are solved in parallel, the computational delay is reduced when compared to standard MPC. This allows for faster sampling that can outperform, in terms of closed-loop cost, a standard MPC formulation. Feasibility and stability are guaranteed by an appropriate selection of so-called blocking matrices.