Robust optimization based on the Propagation of Variance method for analytic design models

Abstract

The robust optimisation is performed in the preliminary design phase dealing with analytic models. The analytic models come either from the finite element models or from the physical laws approximation. The variability on the design parameters is defined using random variables identified by their first two Moments, the Mean and the Standard deviation. A robust design approach is proposed that determines whether a robust design solution exists or not to the given design problem. This approach combines a reformulation of the analytic model with the new design specifications. It integrates the parameter uncertainties (Mean and Standard deviation) and a deterministic optimisation algorithm (SQP algorithm). The Means and the Standard deviation are computed using the Propagation of Variance method. The engineering application of an electrical actuator design is introduced and used to show the implementation and the effectiveness of the proposed robust approach.

Keywords:

• robust design
• analytic model
• Propagation of Variance
• monte carlo
• optimisation