Reduced-order full information estimation observer-based dissipative control for nonlinear discrete-time switched singular systems with unknown inputs

IF 3.5 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2024-12-31 DOI:10.1016/j.amc.2024.129256
Hongpeng Shi, Zhenli Zhao, Shuping Ma
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Abstract

The dissipative control problem for nonlinear discrete-time switched singular systems (NDSSSs) is investigated via a novel reduced-order observer in this paper. Firstly, based on the generalized Sylvester equations and the introduced nonlinear injection term, a novel reduced-order observer is designed for each subsystem. The designed reduced-order observer can still produce accurate full-information estimation even though the dynamics and the output of the systems both contain unknown inputs. Then, by using average dwell-time scheme and multi-Lyapunov functions, some new sufficient conditions are proposed such that the resulted closed-loop NDSSSs are regular and causal, have a unique solution, and are globally uniformly asymptotically stable with a strict (Q,S,V)-γ-dissipative. A novel relaxation technique is proposed for decoupling nonlinear inequalities involving products of multiple nonsquare unknown variables. The design procedures of reduced-order observer and controller are presented by a specific algorithm. Finally, two numerical examples and an electronic circuit example are provided to illustrate the effectiveness of the theoretical results.
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输入未知的非线性离散切换奇异系统的全信息估计减阶耗散控制
利用一种新的降阶观测器,研究了非线性离散切换奇异系统的耗散控制问题。首先,基于广义Sylvester方程和引入的非线性注入项,为各子系统设计了新的降阶观测器;所设计的降阶观测器在系统的动态和输出均包含未知输入的情况下仍能产生准确的全信息估计。然后,利用平均时间格式和多重lyapunov函数,给出了得到的闭环NDSSSs是正则的、因果的、有唯一解的、具有严格(Q,S,V)-γ-耗散的全局一致渐近稳定的一些新的充分条件。针对涉及多个非平方未知变量乘积的非线性不等式,提出了一种新的解耦松弛技术。通过具体的算法给出了降阶观测器和控制器的设计过程。最后,给出了两个数值算例和一个电子电路算例来说明理论结果的有效性。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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