2020/02/17 by Pavel Otta, Otta, Pavel, Ondřej Šantin +3
Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Electrical engineering #Fault Detection and Control Systems #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2002.06835
openalex publication_date 2020/02/17 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
Model Predictive Control (MPC) is a popular optimization-based control\ntechnique. MPC is usually formulated as sparse or dense Quadratic Programming\n(QP). This paper reviews two well-known methods, namely, state condensing and\nmove blocking, and brings them together. Their combination results in\ngeneralized QP that serves arbitrarily sparse (or dense) QP for MPC with move\nblocking. The proposed QP can be solved by a specialized solver capable of\nexploiting a sparsity structure of the problem. Numerical examples give inside\nin computational and memory requirements.\n