Iterative Proportional-Integral Interval Estimation of Linear Discrete-Time Systems

• 成果类型: Article
• 署名作者: Shen, Mouquan; Zhang, Tu; Park, Ju H.; Wang, Qing-Guo; Li, Li-Wei
• 署名单位: Nanjing Tech University; Yeungnam University; Beijing Normal University; Beijing Normal-Hong Kong Baptist University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3203226
• 发表日期: 2023
• 页码: 4249-4256
• 关键词: Terms-Linear systems; Robust control; State estimation

摘要

An iterative proportional-integral interval estimation strategy for linear discrete-time systems is investigated in this article. A sequence iterative proportional-integral observer is built on system output and unknown disturbance iterative estimation. With the help of a structure separation technique, a sufficient condition in terms of linear matrix inequality is proposed to make the observer error system be asymptotically stable. The boundary reachability of the observer error system is analyzed via zonotope. The zonotope-based iterative algorithms, with and without the output integral, are built to generate estimated state intervals. Compared with the existing result, the proposed algorithms render tighter estimation intervals illustrated by a simulation study.