Design of Begian–Melek–Mendel structure-based interval type-2 fuzzy logic systems optimized with backpropagation algorithms

Abstract

As an emerging technology, the efficient and energy conserving process of permanent magnetic drive (PMD) presents high uncertainties. This paper designs a type of Begian–Melek–Mendel (BMM) structure interval type-2 fuzzy logic systems (IT2 FLSs) for PMD process uncertain parameters forecasting. The antecedent, consequent, and input measurements of systems are all selected as the Gaussian type-2 primary membership functions with uncertain standard deviations. Then the backpropagation algorithms are used to tune the parameters of IT2 FLSs. According to the Monte Carlo simulation studies and convergence analysis, the proposed IT2 FLSs are proved to be superior to two corresponding T1 FLSs in generalization ability.

A triangle decomposition method for the mobility control of mecanum wheel-based robots

“…The principle behind this fact is shown in Figure 5. In (7) implies that the length of the path 𝐴𝐵 for reaching the destinantion is inversely proportional to the cosine of the angle of movement β. In other words, the path's length increases with an increasing angle of movement.…”

“…The study provides a unique control strategy using a self-tuning fuzzy logic with PID control, resulting in precise and effective motion control. Chen [7] proposes a backstepping technique supported by a finite-time adaptive interval type-2 fuzzy controller. The technique consists of approximating the dynamics of a mecanum wheel platform using an improved version of the begian-melek-mendel (BMM) algorithm.…”