TY - JOUR
T1 - Efficient Multiobjective Antenna Optimization with Tolerance Analysis Through the Use of Surrogate Models
AU - Easum, John A.
AU - Nagar, Jogender
AU - Werner, Pingjuan L.
AU - Werner, Douglas H.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12
Y1 - 2018/12
N2 - An efficient, black-box multiobjective optimization technique is presented, which is capable of simultaneously optimizing designs for performance as well as robustness when input tolerance values are not known a priori. During the optimization process, adaptive statistical surrogate mappings between input variables and output objectives are formulated within a model selection framework. These statistical models can be evaluated in fractions of a second and serve as an efficient surrogate for a more computationally intensive process, such as an electromagnetic simulation. By exploiting the speed offered from surrogate modeling techniques, new, high-performance designs can be quickly identified. In addition, complete tolerance analysis can be conducted within the optimization loop, which provides designers with critical information regarding the robustness of designs. To demonstrate the effectiveness of this approach, it will be applied to the optimization of a capacitively loaded monopole and a wideband Vivaldi antenna.
AB - An efficient, black-box multiobjective optimization technique is presented, which is capable of simultaneously optimizing designs for performance as well as robustness when input tolerance values are not known a priori. During the optimization process, adaptive statistical surrogate mappings between input variables and output objectives are formulated within a model selection framework. These statistical models can be evaluated in fractions of a second and serve as an efficient surrogate for a more computationally intensive process, such as an electromagnetic simulation. By exploiting the speed offered from surrogate modeling techniques, new, high-performance designs can be quickly identified. In addition, complete tolerance analysis can be conducted within the optimization loop, which provides designers with critical information regarding the robustness of designs. To demonstrate the effectiveness of this approach, it will be applied to the optimization of a capacitively loaded monopole and a wideband Vivaldi antenna.
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U2 - 10.1109/TAP.2018.2870338
DO - 10.1109/TAP.2018.2870338
M3 - Article
AN - SCOPUS:85053353732
SN - 0018-926X
VL - 66
SP - 6706
EP - 6715
JO - IEEE Transactions on Antennas and Propagation
JF - IEEE Transactions on Antennas and Propagation
IS - 12
M1 - 8466860
ER -