论文标题
连续时间模型预测控制的递归可行性而无需稳定约束
Recursive feasibility of continuous-time model predictive control without stabilising constraints
论文作者
论文摘要
我们考虑非线性连续时间控制系统的采样数据模型预测控制（MPC）。我们得出了足够的条件，可以保证递归可行性和渐近稳定性，而无需稳定成本和/或约束。此外，我们提出公式，以根据（本地）成本可控性的概念明确估算预测范围所需的长度。对于线性二次情况，可以从标准假设中推断成本可控性。此外，我们扩展了地平线长度与初始状态与生存力内边界之间的关系的结果，从离散时间到连续时间设置。
We consider sampled-data Model Predictive Control (MPC) of nonlinear continuous-time control systems. We derive sufficient conditions to guarantee recursive feasibility and asymptotic stability without stabilising costs and/or constraints. Moreover, we present formulas to explicitly estimate the required length of the prediction horizon based on the concept of (local) cost controllability. For the linear-quadratic case, cost controllability can be inferred from standard assumptions. In addition, we extend results on the relationship between the horizon length and the distance of the initial state to the boundary of the viability kernel from the discrete-time to the continuous-time setting.
