IFQP: A hybrid optimization method for filter management in fluid power systems under uncertainty

Abstract

An interval-fuzzy quadratic programming (IFQP) method is developed for the assessment of filter allocation and replacement strategies in fluid power systems (FPS) under uncertainty. It can directly handle uncertainties expressed as interval values and/or fuzzy sets that exist in the left-hand and right-hand sides of constraints, as well as in the objective function. Multiple control variables are used to tackle independent uncertainties in the model's right-hand sides and thus optimize the overall satisfaction of the system performance. The IFQP method is applied to a case of planning filter allocation and replacement strategies under uncertainty for an FPS with a single circuit. A piecewise linearization approach is firstly employed to convert the nonlinear FPS problem into a linear one. The generated decision alternatives can help decision makers to identify desired policies for contamination control under various total costs, satisfaction degrees, and system-failure risks under different contaminant-ingression/generation rates.

Keywords:

• contamination control
• fluid power system
• fuzzy quadratic interval
• uncertainty

Acknowledgements

This research was funded by Natural Science Foundations of China (Nos. 50675074 and 50775081), National High-tech R&D (863) Program (No. 2006AA09Z238), NCET of State Education Ministry (No. NCET-07-0330), and PHR (IHLB) 20090203.