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A Takagi-Sugeno system with a Generalized type-2 Fuzzy logic system (SGT2FLS) is utilized to find of parameters in a Bee Colony Optimization (BCO) to control the motion of an autonomous mobile robot (AMR) is presented in this paper. The first objective of BCO algorithm is to find the optimal design of the Membership Functions (MFs) in a Mamdani Generalized Type-2 Fuzzy Logic System (MGT2FLS), the second idea was using a Fuzzy BCO-SGT2FLS to find the optimal values of \(\alpha\) and \(\beta\) parameters in BCO and an analysis of the errors obtained by the Mean Square Error (MSE) metric is presented. The experimentations demonstrate that BCO has an excellent execution when a FBCO-SGT2FLS is executed. In addition, a comparative with a FBCO-MGT2FLS is depicted.

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Analysis Comparative of a Mamdani Versus Takagi-Sugeno Defuzzification Method of a Fuzzy Bee Colony Optimization Algorithm to Stable the Trajectory in an Autonomous Mobile Robot

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  • 发表日期：

    2025年

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  • Leticia Amador-Angulo,
  • Oscar Castillo

摘要

A Takagi-Sugeno system with a Generalized type-2 Fuzzy logic system (SGT2FLS) is utilized to find of parameters in a Bee Colony Optimization (BCO) to control the motion of an autonomous mobile robot (AMR) is presented in this paper. The first objective of BCO algorithm is to find the optimal design of the Membership Functions (MFs) in a Mamdani Generalized Type-2 Fuzzy Logic System (MGT2FLS), the second idea was using a Fuzzy BCO-SGT2FLS to find the optimal values of \(\alpha\) and \(\beta\) parameters in BCO and an analysis of the errors obtained by the Mean Square Error (MSE) metric is presented. The experimentations demonstrate that BCO has an excellent execution when a FBCO-SGT2FLS is executed. In addition, a comparative with a FBCO-MGT2FLS is depicted.