论文标题
分布式系统的随机输出反馈MPC方案
A stochastic output-feedback MPC scheme for distributed systems
论文作者
论文摘要
在本文中，我们提出了一种新型的随机输出反馈MPC方案，用于具有添加过程和测量噪声的分布式系统。概率可达集的概念对其进行了限制，在闭环中保证在障碍分布的单程性假设下可以在闭环中满足。通过调节优化问题的初始状态在可行性上，可以确保递归可行性的基本属性。证明了闭环的机会限制满意度，递归可行性和与渐近平均成本约束的收敛性。本文以三个相互联系的子系统的数值示例结束，与集中设置相比，强调了机会限制满意度和平均成本。
In this paper, we present a novel stochastic output-feedback MPC scheme for distributed systems with additive process and measurement noise. The chance constraints are treated with the concept of probabilistic reachable sets, which, under an unimodality assumption on the disturbance distributions are guaranteed to be satisfied in closed-loop. By conditioning the initial state of the optimization problem on feasibility, the fundamental property of recursive feasibility is ensured. Closed-loop chance constraint satisfaction, recursive feasibility and convergence to an asymptotic average cost bound are proven. The paper closes with a numerical example of three interconnected subsystems, highlighting the chance constraint satisfaction and average cost compared to a centralized setting.
