Design Potential Method for Robust System Parameter Design

Abstract

A novel design potential method that integrates the probabilistic constraint evaluation closely into the design optimization process is presented for robust system parameter design. From a broader perspective, it is shown that the probabilistic constraints can be evaluated using either the conventional reliability index approach or the proposed performance measure approach. The performance measure approach is inherently robust and is more effective when the prohahilistic constraint is inactive. The reliability index approach is more effective for the violated probabilistic constraint, but it could yield singularity when the probabilistic constraint is inactive. Moreover, the close coupling of performance probability analysis and design optimization is illustrated in a proposed unified system space. The design potential method, which is developed to take full advantage of the important design information obtained from the previous probabilistic constraint evaluation, can significantly accelerate the convergence of the reliability-based design optimization process.