Comparative Analysis of Type-1 and Type-2 Fuzzy Controllers: Exploiting Synergies for Improved Control System Performance

• Autor(a) principal: Aguiar, Renato Aparecido
• Data de Publicação: 2023
• Outros Autores: Franco, Ivan Carlos, Leonardi, Fabrizio
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: The Journal of Engineering and Exact Sciences
• Texto Completo: https://periodicos.ufv.br/jcec/article/view/15936
• topic: fuzzy controllers; type-2 fuzzy sets; Footprint of Uncertainty (FOU)

The utilization of fuzzy controllers in control systems has gained significant attention in various fields due to their ability to handle complex and uncertain systems. This paper focuses on comparing the performance of two types of fuzzy controllers: type-1 fuzzy controller and type-2 fuzzy controller. While type-1 fuzzy controllers have been widely studied and applied, the advantages of type-2 fuzzy controllers in dealing with uncertain and ill-defined systems have garnered attention. A thorough analysis and comparison are conducted to investigate the practical benefits of type-2 fuzzy controllers. The study includes an overview of type-1 and type-2 fuzzy sets, followed by the design methodology for the two controllers. The designed controllers are implemented practically, and the results are analyzed and discussed. Previous research studies have shown the potential of type-2 fuzzy controllers to achieve superior performance compared to type-1 controllers. This paper contributes to the existing body of knowledge by presenting empirical evidence and practical insights into the performance of type-2 fuzzy controllers in real-world applications. The findings shed light on the benefits and limitations of utilizing type-2 fuzzy controllers, particularly in scenarios where system knowledge is limited or incomplete. The results of this study provide valuable guidance for control system designers and practitioners in selecting the most appropriate controller for their specific applications. Furthermore, the insights gained from this research contribute to the ongoing exploration and development of fuzzy control systems, enhancing their effectiveness in various domains.