论文标题
可行性调节器，用于扩大线性模型预测控制器的吸引力区域
A Feasibility Governor for Enlarging the Region of Attraction of Linear Model Predictive Controllers
论文作者
论文摘要
本文提出了一种扩大线性模型预测控制器（MPC）吸引区域时的方法，当时在存在时端约束的情况下跟踪分段构恒定参考。它由一个操纵参考命令的可行性州长（FG）组成，以确保MPC反馈定律构成的最佳控制问题仍然可行。基于多目标线性编程的离线多面体投影算法用于计算可行状态和参考命令集。在线，FG的动作是通过求解凸二次程序来计算的。闭环系统显示出满足约束，渐近稳定，显示零偏移跟踪，并显示参考的有限时间收敛性。
This paper proposes a method for enlarging the region of attraction of Linear Model Predictive Controllers (MPC) when tracking piecewise-constant references in the presence of pointwise-in-time constraints. It consists of an add-on unit, the Feasibility Governor (FG), that manipulates the reference command so as to ensure that the optimal control problem that underlies the MPC feedback law remains feasible. Offline polyhedral projection algorithms based on multi-objective linear programming are employed to compute the set of feasible states and reference commands. Online, the action of the FG is computed by solving a convex quadratic program. The closed-loop system is shown to satisfy constraints, be asymptotically stable, exhibit zero-offset tracking, and display finite-time convergence of the reference.
