A Fuzzy Approach for the Kinematic Reliability Assessment of Robotic Manipulators

Abstract

SUMMARY This paper aims at developing a novel method to assess the kinematic reliability of robotic manipulators based on the fuzzy theory. The kinematic reliability quantifies the probability of obtaining positioning errors within acceptable limits. For this purpose, the fuzzy reliability evaluates the effect of the joint clearances on the end-effector position to compute a failure possibility index. As an alternative to the conventional methods reported in the literature, this failure possibility index conveys a novel assessment of the kinematic performance. The numerical results are compared with the well-known probabilistic approach based on the Monte Carlo simulation.

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

“…For PSO, the parameters were suggested by [32]. For the case of the GA and DE, the parameters were set based on previous experience in solving similar problems [33,34]. Some assumptions were defined regarding the numerical application of the evolutionary algorithms:…”

Robust control for a tracked mobile robot based on a finite-time convergence zeroing neural network

“…Therefore, a feasible solution with outstanding convergence performance as well as robustness to handle the nonlinear time-varying control issue of the TMR is imperative in practice. Numerous methodologies and techniques for addressing the tracking control issues of robot systems have been extensively studied and reported, including backstepping control (Ji et al, 2002 ; Gao et al, 2022 ; Sabiha et al, 2022 ), sliding mode control (Ahmed et al, 2021 ; Yin et al, 2021 ), fuzzy control (Lara-Molina and Dumur, 2021 ; Li et al, 2022 ), and neural network (Ding et al, 2018 ; Jin and Qiu, 2022 ).…”