文章基本信息

标题：Robust Soft-Landing Control with Quantized Input
本地全文：下载
作者：Claus Danielson ; Claus Danielson ; Stefano Di Cairano 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：18
页码：35-40
DOI：10.1016/j.ifacol.2016.10.136
语种：English
出版社：Elsevier
摘要：Abstract: We propose a controller architecture for soft-landing control with quantized input. The objective of the soft-landing problem is to achieve precise positioning of a moving object at a target position, while ensuring the velocity decreases as the target is approached. In this paper, we formulate the soft-landing problem as a constrained control problem. Our approach combines traditional convex model predictive control with a rounding rule that quantizes the input. The rounding rule is designed to minimize the error between the requested and quantized inputs. A robust control invariant set is used to ensure that the rounding errors do not lead to constraint violations. We demonstrate our approach for a transportation system case study.
关键词：KeywordsRobust Model Predictive ControlInvariant SetsQuantized Control