Exact Reconstruction of State and Disturbance for General Linear Systems Under Relaxed Conditions

This paper investigates the joint state and disturbance estimation for general linear multi-input multi-output (MIMO) systems that do not satisfy observer matching conditions. Resorting to invariant subspace decomposition, the given system is initially partitioned into two components: a strongly observable subsystem and a strongly detectable subsystem. For strongly observable subsystem, the step-to-step estimation scheme and prescribed-time differentiator are adopted to achieve accelerated state estimation. Cooperated with particular intermediate variables generated by decomposition algorithm, the influence of sluggish internal dynamics on the convergence rate of observers for strongly detectable subsystems is reduced. Moreover, the existence condition of the proposed observer is established. Instead of restrictive observer matching conditions, the proposed observer requires simply strong detectability and several common constraints on disturbance. Finally, three practical examples are provided to illustrate the effectiveness of the results.

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Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3527606
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Exact Reconstruction of State and Disturbance for General Linear Systems Under Relaxed Conditions

Xuejie Que, Guanghao Su, Xin Wang, Zhenlei Wang
IEEE Transactions on Instrumentation and Measurement
Adaptive Control of Nonlinear Systems
article

Exact Reconstruction of State and Disturbance for General Linear Systems Under Relaxed Conditions

Xuejie Que, Guanghao Su, Xin Wang, Zhenlei Wang
article en

Abstract

This paper investigates the joint state and disturbance estimation for general linear multi-input multi-output (MIMO) systems that do not satisfy observer matching conditions. Resorting to invariant subspace decomposition, the given system is initially partitioned into two components: a strongly observable subsystem and a strongly detectable subsystem. For strongly observable subsystem, the step-to-step estimation scheme and prescribed-time differentiator are adopted to achieve accelerated state estimation. Cooperated with particular intermediate variables generated by decomposition algorithm, the influence of sluggish internal dynamics on the convergence rate of observers for strongly detectable subsystems is reduced. Moreover, the existence condition of the proposed observer is established. Instead of restrictive observer matching conditions, the proposed observer requires simply strong detectability and several common constraints on disturbance. Finally, three practical examples are provided to illustrate the effectiveness of the results.

IEEE Transactions on Instrumentation and MeasurementVol. 74
East China University of Science and Technology (CN), Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 99%
Adaptive Control of Nonlinear Systems
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Exact Reconstruction of State and Disturbance for General Linear Systems Under Relaxed Conditions — Xuejie Que, Guanghao Su, et al. · IEEE Transactions on Instrumentation and Measurement (2025) | TGRS Research Map | TGRS