On Strict Causality Conditions for Descriptor Systems With Unknown Inputs

被引:0
作者
Paitandi, Mamoni [1 ]
Gupta, Mahendra Kumar [2 ]
机构
[1] Natl Inst Technol Jamshedpur, Dept Math, Jamshedpur 831014, Jharkhand, India
[2] Indian Inst Technol Bhubaneswar, Dept Math, Khordha 752050, Odisha, India
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Cause effect analysis; Matrix decomposition; Mathematical models; Indexes; Vectors; Trajectory; Control systems; Transforms; Terminology; Systems modeling; Causality; differential-algebraic equations (DAEs); descriptor systems; impulses; strict causality; unknown inputs; OBSERVER DESIGN;
D O I
10.1109/ACCESS.2024.3519982
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article investigates descriptor systems with unknown inputs that are not necessarily regular. The concept of strict causality is introduced to address the impulsive behavior of the system caused by unknown inputs and differentiating control inputs. By applying a decomposition, a reduced system is obtained, from which the unknown inputs are subsequently eliminated. Initially, conditions for causality and strict causality are presented in terms of the coefficient matrices of the reduced systems, both with and without unknown inputs. Using the strict causality of the reduced system, the strict causality condition of the original system is derived. The process to obtain these conditions is based on numerically stable orthogonal transformations. The proposed theory is elaborated with two numerical examples, demonstrating the practical relevance of the approach.
引用
收藏
页码:195544 / 195551
页数:8
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