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Reliability analysis of complex multi-robotic system using GA and fuzzy methodology

机译：基于遗传算法和模糊方法的复杂多机器人系统可靠性分析

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摘要

The objective of the study is to compute various reliability parameters for multi-robotic system, using Real Coded Genetic Algorithms (RCGAs) and Fuzzy Lambda-Tau Methodology (FLTM). The paper contains a new idea about the reliability analysis of robotic system. The optimal values of mean time between failures (MTBF) and mean time to repair (MTTR) are obtained using GAs. Petri Net (PN) tool is applied to represent the interactions among the working components of multi-robotic system. To enhance the relevance of the reliability study, triangular fuzzy numbers (TFNs) are developed from the computed data, using possibility theory. The use of fuzzy arithmetic in the PN model increases the flexibility for application to various systems and conditions. Various reliability parameters, namely failure rate, repair time, MTBF, expected number of failures (ENOF), reliability and availability, are computed using FLTM. Sensitivity analysis has also been performed and the effects on system MTBF are addressed. The adopted methodology improves the shortcomings/drawbacks of the existing probabilistic approaches and gives a better understanding of the system behavior through its graphical representation. The analysis presented, may be helpful for the system analyst to analyze and predict the system behavior and to reallocate the required resources.
机译：该研究的目的是使用实数编码遗传算法（RCGA）和模糊Lambda-Tau方法（FLTM）计算多机器人系统的各种可靠性参数。本文提出了关于机器人系统可靠性分析的新思路。使用GA获得平均故障间隔时间（MTBF）和平均修复时间（MTTR）的最佳值。 Petri Net（PN）工具用于表示多机器人系统工作组件之间的交互。为了提高可靠性研究的相关性，使用可能性理论从计算数据中开发了三角模糊数（TFN）。 PN模型中模糊算法的使用增加了应用于各种系统和条件的灵活性。使用FLTM计算各种可靠性参数，即故障率，维修时间，MTBF，预期故障数（ENOF），可靠性和可用性。还进行了灵敏度分析，并解决了对系统MTBF的影响。所采用的方法改进了现有概率方法的缺点/缺点，并通过其图形表示方式更好地理解了系统行为。提出的分析可能有助于系统分析人员分析和预测系统行为并重新分配所需的资源。

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