Saifuniza S.,
Farsana Muhammed,
- Scholar, Department of Electrical and Electronics Engineering, TKM College of Engineering, Kollam, Kerala, India
- Assisatant Professor, Department of Electrical and Electronics Engineering, TKM College of Engineering, Kollam, Kerala, India
Abstract
This paper presents a comprehensive review of the application of neuro-fuzzy control systems in various industries. Using the combined strengths of neural networks and fuzzy logic, neural-fuzzy control systems emerge as versatile tools to solve challenging control challenges. The paper begins with clarifying the theoretical basis of neural fuzzy systems, and emphasizing their scalability, definition, and robustness. Specific examples in each domain highlight the effectiveness of neuro-fuzzy control in solving real world problems, from trajectory tracking in robots to fault detection in power systems and discuss advances recent in this field, such as deep neuro-fuzzy architectures and various methodologies. Bringing together insights from different disciplines, this paper provides a comprehensive perspective on how neuro-fuzzy control systems are versatile and effective for solving complex control challenges in various industries.
Keywords: Neural network, fuzzy logic, neuro-fuzzy control system, robotics, intelligent modeling
[This article belongs to International Journal of Electro-Mechanics and Material Behaviour ]
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| Volume | 02 | |
| Issue | 01 | |
| Received | 23/05/2024 | |
| Accepted | 14/06/2024 | |
| Published | 26/06/2024 | |
| Publication Time | 34 Days |