Online constraint removal: Accelerating MPC with a Lyapunov function
Online constraint removal: Accelerating MPC with a Lyapunov function
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DOI：
10.1016/j.automatica.2015.04.014
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发表时间：
2015-07
期刊：
影响因子：
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通讯作者：
M. Jost;G. Pannocchia;M. Mönnigmann
中科院分区：
文献类型：
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作者：
M. Jost;G. Pannocchia;M. Mönnigmann
我们展示了如何使用李雅普诺夫函数来加速线性离散时间系统的线性约束和二次成本的MPC。我们的方法预测，在当前的时间步，哪些约束将在下一个时间步不活动。这些约束可以从下一个时间步的在线优化问题中移除。检测无效约束的标准是基于李雅普诺夫函数沿受控系统的轨迹沿着的减少。该准则简单，易于在现有MPC算法中实现，且计算量小。
We show how to use a Lyapunov function to accelerate MPC for linear discrete-time systems with linear constraints and quadratic cost. Our method predicts, in the current time step, which constraints will be inactive in the next time step. These constraints can be removed from the online optimization problem of the next time step. The criterion for the detection of inactive constraints is based on the decrease of the Lyapunov function along the trajectory of the controlled system. The criterion is simple, easy to implement in existing MPC algorithms, and its computational cost is small.