Stability Based Robust Eigenvalue Design for Tolerance

2009 ◽  
Vol 131 (8) ◽  
Author(s):  
XinJiang Lu ◽  
Han-Xiong Li
Keyword(s):  
Robust Design ◽  
Design Method ◽  
Integrated Approach ◽  
System Stability ◽  
Design Parameters ◽  
Complex Eigenvalue ◽  
Sensitivity Matrix ◽  
Eigenvalue Sensitivity ◽  
Design Systems ◽  
Robust Design Method

A novel integrated approach is developed to design systems for stability and robustness. First, design parameters with large variation bounds are chosen to maintain system stability. Then, a robust eigenvalue design problem is considered to make the dynamic response less sensitive to parameter variations. A new complex sensitivity matrix is derived from the system dynamics with the eigenvalue variation approximated into a first-order model by means of the eigenvector orthogonal theory. Through a proper transformation, the complex eigenvalue sensitivity of the Jacobian matrix can still be processed by the traditional robust design approach. By minimizing the eigenvalue sensitivity, design parameters can be obtained for stability as well as robustness. Furthermore, the tolerance space of the selected parameters can be maximized to improve robust performance. A Laval rotor example is used to demonstrate the effectiveness of the proposed robust design method.

scholarly journals Robust optimization design of structures based on the specular reflection algorithm

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401983413
Author(s):  
Qisong Qi ◽  
Qing Dong ◽  
Yunsheng Xin
Keyword(s):  
Robust Design ◽  
Structural Design ◽  
Optimization Design ◽  
Design Method ◽  
Specular Reflection ◽  
Design Parameters ◽  
Theoretical Design ◽  
Recent Advancement ◽  
Robust Optimization Design ◽  
Robust Design Method

The nominal values of structural design parameters are usually calculated using a traditional deterministic optimization design method. However, owing to the failure of this type of method to consider potential variations in design parameters, the theoretical design results can be far from reality. To address this problem, the specular reflection algorithm, a recent advancement in intelligence optimization, is used in conjunction with a robust design method based on sensitivity. This method not only is able to fully consider the influence of parameter uncertainty on the design results but also has strong applicability. The effectiveness of the proposed method is verified by numerical examples, and the results show that the robust design method can significantly improve the reliability of the structure.

scholarly journals Multilayer Machine Learning-Assisted Optimization-Based Robust Design and Its Applications to Antennas and Arrays

2020 ◽  
Author(s):  
Weiqi Chen ◽  
Qi Wu ◽  
Chen Yu ◽  
Haiming Wang ◽  
Wei Hong
Keyword(s):  
Machine Learning ◽  
Design Process ◽  
Robust Design ◽  
Design Method ◽  
Computation Time ◽  
Design Parameters ◽  
Worst Case Analysis ◽  
Worst Case ◽  
And Performance ◽  
Robust Design Method

An efficient multilayer machine learning-assisted optimization (ML-MLAO)-based robust design method is proposed for antenna and array applications. Machine learning methods are introduced into multiple layers of the robust design process, including worst-case analysis (WCA), maximum input tolerance hypervolume (MITH) searching, and robust optimization, considerably accelerating the whole robust design process. First, based on a surrogate model mapping between the design parameters and performance, WCA is performed using a genetic algorithm to ensure reliability. MITH searching is then carried out using a double-layer MLAO (DL-MLAO) framework to find the MITH of the given design point. Next, based on the training set obtained using DL-MLAO, correlations between the design parameters and the MITH are learned. The robust design is carried out using surrogate models for both the performance and the MITH, and these models are updated online following the ML-MLAO scheme. Furthermore, two examples, including an array synthesis problem and an antenna design problem, are used to verify the proposed ML-MLAO method. Finally, the numerical results and computation time are discussed to demonstrate the effectiveness of the proposed method.

scholarly journals Multilayer Machine Learning-Assisted Optimization-Based Robust Design and Its Applications to Antennas and Arrays

2020 ◽  
Author(s):  
Weiqi Chen ◽  
Qi Wu ◽  
Chen Yu ◽  
Haiming Wang ◽  
Wei Hong
Keyword(s):  
Machine Learning ◽  
Design Process ◽  
Robust Design ◽  
Design Method ◽  
Computation Time ◽  
Design Parameters ◽  
Worst Case Analysis ◽  
Worst Case ◽  
And Performance ◽  
Robust Design Method

An efficient multilayer machine learning-assisted optimization (ML-MLAO)-based robust design method is proposed for antenna and array applications. Machine learning methods are introduced into multiple layers of the robust design process, including worst-case analysis (WCA), maximum input tolerance hypervolume (MITH) searching, and robust optimization, considerably accelerating the whole robust design process. First, based on a surrogate model mapping between the design parameters and performance, WCA is performed using a genetic algorithm to ensure reliability. MITH searching is then carried out using a double-layer MLAO (DL-MLAO) framework to find the MITH of the given design point. Next, based on the training set obtained using DL-MLAO, correlations between the design parameters and the MITH are learned. The robust design is carried out using surrogate models for both the performance and the MITH, and these models are updated online following the ML-MLAO scheme. Furthermore, two examples, including an array synthesis problem and an antenna design problem, are used to verify the proposed ML-MLAO method. Finally, the numerical results and computation time are discussed to demonstrate the effectiveness of the proposed method.

Reliability-Based Optimization and Robust Design of a Coil Tube-Spring with Non-Normal Distribution Parameters

2005 ◽  
Vol 219 (6) ◽  
pp. 567-575 ◽  
Author(s):  
Y. M. Zhang ◽  
X. D. He ◽  
Q. L. Liu ◽  
B. C. Wen
Keyword(s):  
Normal Distribution ◽  
Robust Design ◽  
Design Method ◽  
Design Parameters ◽  
Edgeworth Series ◽  
Reliability Sensitivity ◽  
Distribution Parameters ◽  
Reliability Based Optimization ◽  
Robust Design Method ◽  
First Four Moments

This paper proposes the application of reliability-based optimization and robust design methods of a coil tube-spring. The perturbation method, the Edgeworth series, the reliability-based optimization, the reliability sensitivity technique, and the robust design method are employed to present practical and effective approaches of reliability-based optimization and robust design for coil tube-spring with non-normal distribution parameters, on the condition of the known first four moments of the original random variables. Theoretical formulae for reliability-based optimization and robust design are obtained. The respective programmes can be used to obtain the reliability-based optimization and robust design parameters of a coil tube-spring with non-normal distribution parameters accurately and quickly.

scholarly journals Novel Robust Design Method of Multilayer Optical Coatings

ISRN Optics ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Suyong Wu ◽  
Xingwu Long ◽  
Kaiyong Yang
Keyword(s):  
Robust Design ◽  
Optimization Design ◽  
Design Method ◽  
Analytical Calculation ◽  
Design Procedure ◽  
Deposition Process ◽  
Practical Significance ◽  
Optical Coatings ◽  
Optical Films ◽  
Robust Design Method

We present a novel fast robust design method of multilayer optical coatings. The sensitivity of optical films to production errors is controlled in the whole optimization design procedure. We derive an analytical calculation model for fast robust design of multilayer optical coatings. We demonstrate its effectiveness by successful application of the robust design method to a neutral beam splitter. It is showed that the novel robust design method owns an inherent fast computation characteristic and the designed film is insensitive to the monitoring thickness errors in deposition process. This method is especially of practical significance to improve the mass production yields and repetitive production of high-quality optical coatings.

Robust Layout Synthesis of a MEM Crab-Leg Resonator Using a Constrained Genetic Algorithm

2007 ◽  
Author(s):  
Zhun Fan ◽  
Sofiane Achiche
Keyword(s):  
Genetic Algorithm ◽  
Robust Design ◽  
Optimization Problem ◽  
Design Method ◽  
Research Work ◽  
Constrained Optimization Problem ◽  
Geometric Uncertainties ◽  
Layout Synthesis ◽  
Target Performance ◽  
Robust Design Method

The research work carried out in this paper introduces a robust design method for layout synthesis of MEM resonator subject to inherent geometric uncertainties such as the fabrication error on the sidewall of the structure. The robust design problem is formulated as a multi-objective constrained optimization problem with certain assumptions and treated by a special constrained genetic algorithm. The MEM design used for validation is a crab-leg resonator taken from the literature. The results show that the approach proposed in this research can lead to design results that meet the target performance and are less sensitive to geometric uncertainties than typical designs.

Sign in / Sign up

Export Citation Format

Share Document