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Model Predictive Control (MPC) is a popular optimization-based controltechnique. MPC is usually formulated as sparse or dense Quadratic Programming(QP). This paper reviews two well-known methods, namely, state condensing andmove blocking, and brings them together. Their combination results ingeneralized QP that serves arbitrarily sparse (or dense) QP for MPC with moveblocking. The proposed QP can be solved by a specialized solver capable ofexploiting a sparsity structure of the problem. Numerical examples give insidein computational and memory requirements.

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