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Filter allocation and replacement strategies in fluid power system under uncertainty: a fuzzy robust nonlinear programming approach

机译:不确定条件下流体动力系统中的滤波器分配与替换策略:模糊鲁棒非线性规划方法

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摘要

A fuzzy robust nonlinear programming model is developed for the assessment of filter allocation and replacement strategies in hydraulic systems under uncertainty. It integrates the methods of fuzzy mathematic programming (FMP) and robust programming (RP) within the mixed integer nonlinear programming framework, and can facilitate dynamic analysis and optimization of filters allocation and replacement planning where the uncertainties are expressed as fuzzy membership functions. In modeling formulation, theory of contamination wear of typical hydraulic components is introduced to strengthen the presentation of relationship between system contamination and work performance. The fuzzy decision space is delimited into a more robust one by specifying the uncertainties through dimensional enlargement of the original fuzzy constraints. The piecewise linearization approach is employed to handle the nonlinearities of problem. The developed method has been applied to a case of planning filter allocation and replacement strategies under uncertainty and the generated optimal solution will help to reduce the total system cost and failure-risk level of the FPS.
机译:建立了模糊鲁棒非线性规划模型,用于评估不确定性条件下液压系统的过滤器分配和更换策略。它在混合整数非线性规划框架内集成了模糊数学规划(FMP)和鲁棒规划(RP)的方法,并且可以在不确定性表示为模糊隶属函数的情况下,促进动态分析和优化滤波器分配和替换计划。在建模公式中,引入了典型液压部件的污染磨损理论,以加强系统污染与工作性能之间关系的表述。通过通过原始模糊约束的尺寸放大来指定不确定性,将模糊决策空间划分为一个更鲁棒的空间。采用分段线性化方法来处理问题的非线性。所开发的方法已应用于不确定情况下规划过滤器分配和更换策略的情况,并且所生成的最佳解决方案将有助于降低FPS的总系统成本和故障风险水平。

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