论文标题
多次限制非线性过程的收缩约束模型预测控制
A Contraction-constrained Model Predictive Control for Multi-timescale Nonlinear Processes
论文作者
论文摘要
许多化学过程都表现出不同的时间尺度动力学，并且在时间尺度敏感变量之间具有很强的耦合。具有非均匀间隔优化范围的模型预测控制是一种有效的多种仪表控制的方法，并提供了降低计算复杂性的机会。在这种方法中，可以通过在预测范围的早期实现较小的时间间隔以及在预测结束时越来越较大的时间间隔，可以将快速，中等和缓慢的动态包含在优化问题中。在本文中，基于收缩理论开发了一种参考性的条件，以在非均匀预测范围内为非线性系统提供稳定性保证。
Many chemical processes exhibit diverse timescale dynamics with a strong coupling between timescale sensitive variables. Model predictive control with a non-uniformly spaced optimisation horizon is an effective approach to multi-timescale control and offers opportunities for reduced computational complexity. In such an approach the fast, moderate and slow dynamics can be included in the optimisation problem by implementing smaller time intervals earlier in the prediction horizon and increasingly larger intervals towards the end of the prediction. In this paper, a reference-flexible condition is developed based on the contraction theory to provide a stability guarantee for a nonlinear system under non-uniform prediction horizons.
