Farsana Muhammed
Saifuniza S
- Assiatant Professor Department of Electrical and Electronics Engineering, TKM College of Engineering Kollam India
- Student Department of Electrical and Electronics Engineering, TKM College of Engineering Kollam 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 It 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 Hybrid Intelligence Systems for Advanced Control and Automation.
Keywords: Neural network, fuzzy logic, neuro-fuzz, robotics, intelligent modeling
[This article belongs to International Journal of Electro-Mechanics and Material Behavior(ijemb)]
Browse Figures
References
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| Volume | 02 |
| Issue | 01 |
| Received | May 23, 2024 |
| Accepted | June 14, 2024 |
| Published | July 12, 2024 |
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