Robust Optimization Utilizing the Second-Order Design Sensitivity Information

• Published in: IEEE transactions on magnetics Vol. 46; no. 8; pp. 3117 - 3120
• Main Authors: Kim, Nam-Kyung, Kim, Dong-Hun, Kim, Dong-Wook, Kim, Heung-Geun, Lowther, David A., Sykulski, Jan K.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 01-08-2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computer science; Constraint optimization; Cross-disciplinary physics: materials science; rheology; Design optimization; Devices; Electromagnetic devices; Exact sciences and technology; Feasibility; Magnetism; Manufacturing; Material properties; Materials science; Mathematical analysis; Methodology; Optimization; Optimization methods; Other topics in materials science; Physics; robust optimization; Robustness; Sensitivity analysis; Testing; Workshops; Design; Second order; sensitivity analysis; Optimization; robust optimization; Magnetic properties
• ISSN: 0018-9464; 1941-0069
• DOI: 10.1109/TMAG.2010.2043719

This paper presents an effective methodology for robust optimization of electromagnetic devices. To achieve the goal, the method improves the robustness of the minimum of the objective function chosen as a design solution by minimizing the second-order sensitivity information, called a gradient index (GI) and defined by a function of gradients of performance functions with respect to uncertain variables. The constraint feasibility is also enhanced by adding a GI corresponding to the constraint value. The distinctive feature of the method is that it requires neither statistical information on design variables nor calculation of the performance reliability during the robust optimization process. The validity of the proposed method is tested with the TEAM Workshop Problem 22.