Imperial College London
In this paper the authors propose the use of parallel computing architectures (multi-core, FPGA and 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.