On the Quadratic Programming Solution for Model Predictive Control with Move Blocking

Model Predictive Control (MPC) is a popular optimization-based control technique. MPC is usually formulated as sparse or dense Quadratic Programming (QP). This paper reviews two well-known methods: state condensing and move blocking, and brings them together. Their combination results in general QP that serves arbitrarily sparse (or dense) QP for MPC with move blocking. The proposed QP can be solved by a specialized solver capable of exploiting a problem's sparsity structure. A numerical example illustrates connections to computational and memory requirements.