论文标题
通过Min-Max方法进行自触发的MPC强大到有限的数据包丢失：扩展版本
Self-triggered MPC robust to bounded packet loss via a min-max approach: extended version
论文作者
论文摘要
网络控制系统通常具有有限的通信带宽，因此在设计基础控制和触发法律时需要特别注意。一种允许在通信流量以及状态和输入上考虑硬性约束的方法是自触发的模型预测控制（MPC）。在此方案中，使用系统行为的预测主动确定采样间隔的最佳长度。但是，以前的自触发MPC的表述忽略了数据包丢失的广泛现象，因此这些方法在实践中可能会失败。在本文中，我们提出了一种新型的自触发的MPC方案，该方案可通过最小最大优化问题来对有限的数据包丢失。对于任何可能的数据包损耗实现，我们证明了递归的可行性，约束满意度和与原点的收敛性，这与界定性约束一致，并在数值示例中证明了所提出的方案的优势。
Networked Control Systems typically come with a limited communication bandwidth and thus require special care when designing the underlying control and triggering law. A method that allows to consider hard constraints on the communication traffic as well as on states and inputs is self-triggered model predictive control (MPC). In this scheme, the optimal length of the sampling interval is determined proactively using predictions of the system behavior. However, previous formulations of self-triggered MPC have neglected the widespread phenomenon of packet loss, such that these approaches might fail in practice. In this paper, we present a novel self-triggered MPC scheme which is robust to bounded packet loss by virtue of a min-max optimization problem. We prove recursive feasibility, constraint satisfaction and convergence to the origin for any possible packet loss realization consistent with the boundedness constraint, and demonstrate the advantages of the proposed scheme in a numerical example.
