sensors-logo

Journal Browser

Journal Browser

Sensor-Based State Estimation and Fault Diagnosis in Automatic Control

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".

Deadline for manuscript submissions: 20 October 2025 | Viewed by 2174

Special Issue Editor


E-Mail Website
Guest Editor
College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
Interests: unknown input observer design; disturbance observer design; fault diagnosis; fault detection and fault-tolerant control; security control for CPS; security state estimation; cooperative control for multi-agent system; attack detection for CPS and MAS; T-S fuzzy model control; sliding mode robust control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

For most practical control systems, state information is difficult or expensive to be totally measured by sensors. One of the alternatives for solving this problem is trying to obtain the full state estimation by partially measuring state information through a reasonable sensor layout. In fact, the concept of the state estimator or observer was developed by Luenberger in the 1960s. Additionally, practical control systems are inevitable with uncertainties, including system parameter variation, external disturbance and fault signal, which can all be regarded as unknown inputs impacting the system. Therefore, designing a state observer to estimate the system state in the presence of unknown inputs, which is also called an unknown input observer (UIO), is a challenging issue. In fact, just after the Luenberger observer was developed, UIO design issues were raised. Since the Luenberger observer was developed, the designs of all kinds of observers, including adaptive observers, robust observers, sliding model observers and UIOs, have attracted researchers’ attentions.

On the other hand, state estimation techniques have already played an important role in control engineering designs. In addition to the original application for state feedback controller design purpose, one of the other major applications of state estimation techniques or observers is observer-based actual and sensor fault diagnosis, including fault detection, fault reconstruction and fault-tolerant control. In fact, observer-based fault diagnosis becomes one of the major methods in model-based fault diagnosis techniques, and investigations on this issue are still a meaningful but challenging open task.

The topics for this Special Issue include (but are not limited to) the following:

  • Observer designs, especially designs of UIOs, interval observers and distributed observers for multiple sensor systems;
  • Observer-based actual and sensor fault diagnosis, including fault detection, fault reconstruction and fault-tolerant control;
  • Malicious attack detection and secure control problem discussions in view of cyber–physic systems (CPSs) or multiple-agent systems (MASs);
  • The applications of observers in real engineering developments.

Prof. Dr. Fanglai Zhu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • state observer
  • disturbance observer
  • UIO
  • distributed observer
  • fault detection
  • fault reconstruction
  • fault-tolerant control
  • attack detection and secure control
 

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

23 pages, 6840 KiB  
Article
A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction
by Muhammad Farooq Siddique, Faisal Saleem, Muhammad Umar, Cheol Hong Kim and Jong-Myon Kim
Sensors 2025, 25(9), 2712; https://doi.org/10.3390/s25092712 - 25 Apr 2025
Viewed by 220
Abstract
This study presents a hybrid deep learning approach for bearing fault diagnosis that integrates continuous wavelet transform (CWT) with an attention-enhanced spatiotemporal feature extraction framework. The model combines time-frequency domain analysis using CWT with a classification architecture comprising multi-head self-attention (MHSA), bidirectional long [...] Read more.
This study presents a hybrid deep learning approach for bearing fault diagnosis that integrates continuous wavelet transform (CWT) with an attention-enhanced spatiotemporal feature extraction framework. The model combines time-frequency domain analysis using CWT with a classification architecture comprising multi-head self-attention (MHSA), bidirectional long short-term memory (BiLSTM), and a 1D convolutional residual network (1D conv ResNet). This architecture effectively captures both spatial and temporal dependencies, enhances noise resilience, and extracts discriminative features from nonstationary and nonlinear vibration signals. The model is initially trained on a controlled laboratory bearing dataset and further validated on real and artificial subsets of the Paderborn bearing dataset, demonstrating strong generalization across diverse fault conditions. t-SNE visualizations confirm clear separability between fault categories, supporting the model’s capability for precise and reliable feature learning and strong potential for real-time predictive maintenance in complex industrial environments. Full article
Show Figures

Figure 1

15 pages, 5551 KiB  
Article
Online Nodal Demand Estimation in Branched Water Distribution Systems Using an Array of Extended Kalman Filters
by Francisco-Ronay López-Estrada, Leonardo Gómez-Coronel, Lizeth Torres, Guillermo Valencia-Palomo, Ildeberto Santos-Ruiz and Arlette Cano
Sensors 2025, 25(8), 2632; https://doi.org/10.3390/s25082632 - 21 Apr 2025
Viewed by 178
Abstract
This paper proposes a model-based methodology to estimate multiple nodal demands by using only pressure and flow rate measurements, which should be recorded at the inlet of the distribution system. The algorithm is based on an array of multiple extended Kalman filters (EKFs) [...] Read more.
This paper proposes a model-based methodology to estimate multiple nodal demands by using only pressure and flow rate measurements, which should be recorded at the inlet of the distribution system. The algorithm is based on an array of multiple extended Kalman filters (EKFs) in a cascade configuration. Each EKF functions as an unknown input observer and focuses on a section of the pipeline. The pipeline model used to design the filters is an adaptation of the well-known rigid water column model. Simulation and experimental tests on standardized pipeline systems are presented to demonstrate the proposed method’s effectiveness. Finally, for the case of the experimental validation, both steady-state and variable input conditions were considered. Full article
Show Figures

Figure 1

19 pages, 775 KiB  
Article
Distributed Consensus Control for Discrete-Time T–S Fuzzy Multiple-Agent Systems Based on an Unknown Input Observer
by Xufeng Ling, Haichuan Xu, Weijie Weng and Fanglai Zhu
Sensors 2024, 24(24), 8149; https://doi.org/10.3390/s24248149 - 20 Dec 2024
Viewed by 515
Abstract
This paper investigates a consensus problem for a class of T–S fuzzy multiple-agent systems (MASs) with unknown input (UI). To begin with, an unknown input observer (UIO) is able to asymptotically estimate the system state and the UI is designed for each agent. [...] Read more.
This paper investigates a consensus problem for a class of T–S fuzzy multiple-agent systems (MASs) with unknown input (UI). To begin with, an unknown input observer (UIO) is able to asymptotically estimate the system state and the UI is designed for each agent. In order to construct the UIO, the state interval estimation is obtained by first using zonotope theory. Next, using the interval estimation of the state, a correlation of the state and the UI is built. Subsequently, a UIO is constructed, which is proposed by building upon the algebraic relationship. Moreover, by using the estimations of the state and the UI, a distributed control protocol is developed based on the proposed UIO. And, with the proposed distributed control protocol, the T–S fuzzy MAS can achieve consensus, in that all the states of the agents can converge to the leader’s state asymptotically. Finally, the effectiveness of the proposed method is demonstrated through two simulation examples. Full article
Show Figures

Figure 1

16 pages, 1773 KiB  
Article
Robust Distributed Observers for Simultaneous State and Fault Estimation over Sensor Networks
by Dingguo Liang, Yunxiao Ren, Yuezu Lv and Silong Wang
Sensors 2024, 24(23), 7589; https://doi.org/10.3390/s24237589 - 27 Nov 2024
Viewed by 800
Abstract
This paper focuses on simultaneous estimation of states and faults for a linear time-invariant (LTI) system observed by sensor networks. Each sensor node is equipped with an observer, which uses only local measurements and local interaction with neighbors for monitoring. The observability of [...] Read more.
This paper focuses on simultaneous estimation of states and faults for a linear time-invariant (LTI) system observed by sensor networks. Each sensor node is equipped with an observer, which uses only local measurements and local interaction with neighbors for monitoring. The observability of said observer is analyzed where non-local observability of a sensor node is required in terms of the system state and faults. The distributed observers present features of H performance to constrain the influence of disturbances on the estimation errors, for which the global design condition is transformed into a linear matrix inequality (LMI). The LMI is proven to be solvable given collective observability of the system and a suitable H performance index. Moreover, in the case that no disturbances exist, fully distributed observers with adaptive gains are designed to asymptotically estimate the states and faults without using any global information from the network. Finally, the effectiveness of the proposed methods is verified through case studies on a spacecraft’s attitude control system. Full article
Show Figures

Figure 1

Back to TopTop