具有移动阻塞的模型预测控制的二次规划解
On the Quadratic Programming Solution for Model Predictive Control with Move Blocking
摘要：
模型预测控制（MPC）是一种流行的基于优化的控制技术。MPC通常表示为稀疏或密集二次规划（QP）。本文回顾了两种常用的方法，即状态压缩和移动阻塞，并将它们结合在一起。它们的组合导致广义QP，其为具有移动阻塞的MPC提供任意稀疏（或密集）QP。所提出的QP可以通过能够利用问题的稀疏结构的专门求解器来求解。数值算例给出了计算量和内存要求。
英文摘要：
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, namely, state condensing and move blocking, and brings them together. Their combination results in generalized 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 sparsity structure of the problem. Numerical examples give inside in computational and memory requirements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
