Abstract Move blocking is an input parameterization scheme that fixes the decision variables over arbitrary time intervals, commonly referred to as blocks, and it is widely implemented in model predictive control (MPC) to reduce the computational load during on-line optimization. Since the blocking position acts as the search direction in the solution space, selection of the blocking structure has a significant effect on the optimality of moved blocked MPC. However, existing move blocked MPC schemes apply arbitrary time-invariant blocking structures without considering the optimality of the blocking structure due to the difficulty in deriving a proper time-varying blocking structure on-line. Thus, we propose a semi-explicit approach for move blocked MPC that solves a multiparametric program for the blocking position set off-line and a simplified on-line optimization problem. This approach allows for a proper time-varying blocking structure for the current state on-line. The proposed approach can efficiently improve the optimality performance of move blocked MPC with only a little additional computational cost for critical region search while guaranteeing the recursive feasibility and closed-loop stability.

中文翻译：

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使用半显式方法应用时变分块结构，以改进的最优性移动分块模型预测控制

摘要 移动块是一种输入参数化方案，它在任意时间间隔内固定决策变量，通常称为块，它被广泛应用于模型预测控制（MPC）中，以减少在线优化过程中的计算量。由于阻塞位置作为解空间中的搜索方向，阻塞结构的选择对移动阻塞MPC的最优性有显着影响。然而，由于难以在线推导出合适的时变阻塞结构，现有的移动阻塞MPC方案应用任意的时不变阻塞结构而没有考虑阻塞结构的最优性。因此，我们提出了一种用于移动阻塞 MPC 的半显式方法，该方法解决了离线阻塞位置集的多参数程序和简化的在线优化问题。这种方法允许为当前在线状态提供适当的时变阻塞结构。所提出的方法可以有效地提高移动阻塞 MPC 的最优性能，同时为关键区域搜索增加很少的计算成本，同时保证递归可行性和闭环稳定性。