Symmetry and Asymmetry in Cyber–Physical Systems

Dear Colleagues,

Cyber–physical systems (CPSs) are characterized by the intimate coupling of computational algorithms with physical processes, forming the backbone of modern industrial automation, intelligent manufacturing, smart infrastructure, and biomedical engineering. In such systems, symmetry and asymmetry are fundamental and pervasive: the symmetric architectures of networked sensors and actuators coexist with inherently asymmetric phenomena such as imbalanced fault data, non-uniform degradation patterns, asymmetric information flows between monitoring nodes, and uneven computational loads across edge–cloud hierarchies.

A critical challenge in CPSs lies in fault diagnosis and intelligent system health management—ensuring the safety, integrity, and longevity of complex engineering systems across industrial, biomedical, and infrastructure domains. This requires intelligent innovations that integrate advanced signal processing, deep learning, and data-driven modeling for real-time damage detection, degradation assessment, and remaining useful life prediction. The interplay between symmetry and asymmetry is deeply embedded in the following tasks: symmetric network topologies versus asymmetric fault propagation paths, balanced training objectives versus imbalanced fault sample distributions, and symmetric physical models versus asymmetry-inducing wear and environmental effects.

This Special Issue invites original research that reveals, exploits, or addresses the symmetric and asymmetric structures in cyber–physical systems, with a particular emphasis on intelligent fault diagnosis, prognostics, and health management. Topics of interest include, but are not limited to:

• Symmetry and asymmetry in CPS architectures: security, stability analysis, and resilience of networked control systems;
• Data asymmetry and imbalanced learning for fault classification and prognostics in CPSs;
• Symmetric and asymmetric signal processing methods for real-time fault detection and diagnosis;
• Digital twin-enabled condition monitoring exploiting structural symmetry of CPS models;
• Asymmetric degradation pattern recognition and remaining useful life prediction;
• Multi-sensor and multi-source data fusion with information asymmetry in IoT-driven monitoring systems;
• Deep learning and AI-based diagnostic methods leveraging symmetry properties (e.g., equivariant neural networks, symmetric loss functions, and invariant feature extraction);
• Physics-informed machine learning for structural and mechanical systems with symmetric/asymmetric constraints;
• Node state estimation and distributed filtering under asymmetric communication topologies;
• Non-cooperative game-theoretic approaches with information asymmetry for CPS security and fault-tolerant control;
• Symmetry-breaking phenomena in degradation and failure processes and their mathematical modeling;
• Graph-based and topological approaches leveraging symmetry in sensor networks for health monitoring;
• Cross-domain applications in medical device reliability, healthcare system monitoring, and smart rehabilitation equipment;
• Novel algorithms validated through experimental or field data demonstrating symmetric/asymmetric properties in CPSs.

Contributions that demonstrate novel algorithms validated through experimental or field data are particularly welcome. We welcome original research articles, comprehensive reviews, and short communications.

Dr. Xiuxiu Ren
Dr. Xiaoguang Zhang
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly 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 2400 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.

• cyber–physical systems
• symmetry and asymmetry
• fault diagnosis and prognostics
• data asymmetry and imbalanced fault detection
• mechanical and structural health monitoring
• deep learning for signal processing
• digital twin and IoT-based intelligent monitoring
• asymmetric degradation modeling
• multi-sensor data fusion with information asymmetry
• node state estimation
• non-cooperative games
• security and automation
• AI-driven healthcare and rehabilitation system innovation
• stability analysis