Applications of Chaos Theory to Complex Systems Analysis in Engineering
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: 19 January 2025 | Viewed by 1274
Special Issue Editors
Interests: embedded systems; chaos analysis; artificial intelligence; drones; high-performance computing
Interests: mechanical engineering; chaos analysis; signal processing; sound analysis; vibration
Special Issue Information
Dear Colleagues,
In the field of engineering, the application of chaos theory holds profound importance in understanding and managing complex systems. Chaos theory's significance stems from its ability to unravel the intricate dynamics of nonlinear systems, a common occurrence in real-world engineering problems.
Chaos theory aids engineers in comprehending the complexities of nonlinear behavior, providing a deeper understanding of systems such as fluid dynamics, electrical circuits, and weather patterns. It introduces the concept of deterministic chaos, allowing engineers to predict the seemingly random behaviors in deterministic systems. This predictive power is invaluable in safety-critical applications like aerospace design.
Moreover, chaos theory offers tools for optimizing and controlling complex systems. Engineers can use chaos control techniques to stabilize chaotic systems and enhance overall system performance. This capability has applications in various domains, including robotics, power grids, and chemical processes.
Additionally, chaos theory fosters innovation by encouraging creative problem solving and the exploration of unconventional solutions. It equips engineers with the tools to design more resilient systems by analyzing responses to disturbances and external factors.
This Special Issue focuses on publishing new and improved techniques to analyze low-dimensional chaotic dynamics, as well as complex interacting systems (e.g., flocks and networks), mainly presenting how chaos theory empowers engineers to navigate challenges, predict and manage unpredictability, optimize performance, drive innovation, and build robust and resilient systems. The authors are encouraged (but not limited) to discuss entropy-related aspects of chaos theory, for example, entropy and information theory, sensitivity to initial conditions, entropy as a measure of uncertainty, chaos in statistical mechanics, and quantification of chaos and entropy. Common applications of entropy and chaos theory in engineering are as follows:
- Dynamical system analysis;
- Vibrational analysis;
- Fluid dynamics;
- Control systems;
- Communication systems;
- Environmental engineering;
- Electronic circuits;
- Secure communication and cryptography;
- Energy and power systems;
- Aeronautics and space exploration;
- Biomedical engineering;
- Materials science;
- Quality control.
Prof. Dr. Alisson Brito
Prof. Dr. Abel Cavalcante Lima Filho
Prof. Dr. Jorge Gabriel G. S. Ramos
Guest Editors
Manuscript Submission Information
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Keywords
- nonlinearity
- complex systems
- detection and diagnosis of failure
- deterministic chaos
- predictability
- optimization
- control
- robustness
- resilience
- fault tolerance
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