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Chaos in Control Systems: A Review of Suppression and Induction Strategies with Industrial Applications

Asad Shafique, Georgii Kolev

2025Englishchaos controlnonlinear dynamicscontrol systemsstabilityindustrial applicationsartificial intelligence

Abstract

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In control systems, chaos is a natural dualistic phenomenon that can be both a beneficial resource to be used and a negative phenomenon to be avoided. The study examines two opposing paradigms: positive chaotic control, which aims to enhance performance, and negative chaos management, which aims to stabilize a system. More sophisticated suppression methods, including adaptive neural networks, sliding mode control, and model predictive control, can decrease convergence times. Controlled chaotic dynamics have significantly impacted the domain of embedded control systems. Specialized controller designs include fractal-based systems and hybrid switching systems that offer better control of chaotic behavior in many situations. The paper highlights the key issues that are related to chaos-based systems, such as the need to implement them in real time, parameter sensitivity, and safety. Recent research suggests an increased interdependence between artificial intelligence, quantum computing, and sustainable technology. The synthesis shows that chaos control has evolved into an engineering field, significantly impacting the industrial landscape.

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Cite This Work

@article{0546dadf-6f64-40e2-b8e1-dbc08f0d1eea,
  title={Chaos in Control Systems: A Review of Suppression and Induction Strategies with Industrial Applications},
  author={Asad Shafique and Georgii Kolev},
  year={2025},
  language={English}
}
TY  - JOUR
TI  - Chaos in Control Systems: A Review of Suppression and Induction Strategies with Industrial Applications
AU  - Asad Shafique
AU  - Georgii Kolev
PY  - 2025
LA  - English
ER  -

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