Aeroservoelastic structural and control optimization using classical and modern robust design schemes

Author(s):  
Boris Moulin ◽  
Moshe Idan ◽  
Mordechay Karpel
Author(s):  
Sulaiman F. Alyaqout ◽  
Panos Y. Papalambros ◽  
A. Galip Ulsoy

System performance can significantly benefit from optimally integrating the design and control of engineering systems. To improve the robustness properties of systems, the present article introduces an approach that combines robust design with robust control and investigates the coupling between them. However, the computational cost of improving this robustness can often be high due to the need to solve a resulting minimax design and control optimization problem. To reduce this cost, sequential and iterative strategies are proposed and compared to an all-in-one strategy for solving the minimax problem. These strategies are then illustrated for a case-study: Robust design and robust control of a DC motor. Results show that the resulting strategies can improve the robustness properties of the DC motor. In addition, the coupling strength between robust design and robust control tends to increase as the applied level of uncertainty increases.


2002 ◽  
Vol 25 (1) ◽  
pp. 152-159 ◽  
Author(s):  
Boris Moulin ◽  
Moshe Idan ◽  
Mordechay Karpel

Author(s):  
X H Wang ◽  
H T Chen ◽  
X X Zhu ◽  
J L Zhang ◽  
W L Liu ◽  
...  

Author(s):  
Mohammad Salehian ◽  
Morteza Haghighat Sefat ◽  
Khafiz Muradov

2011 ◽  
Vol 133 (9) ◽  
Author(s):  
Diane L. Peters ◽  
P. Y. Papalambros ◽  
A. G. Ulsoy

Optimal system design of “smart” products requires optimization of both the artifact and its controller. When the artifact and the controller designs are independent, the system solution is straightforward through sequential optimization. When the designs are coupled, combined simultaneous optimization can produce system-optimal results, but presents significant computational and organizational complexity. This paper presents a method that produces results comparable with those found with a simultaneous solution strategy, but with the simplicity of the sequential strategy. The artifact objective function is augmented by a control proxy function (CPF), representing the artifact’s ease of control. The key to successful use of this method is the selection of an appropriate CPF. Four theorems that govern the choice and evaluation of a CPF are given. Each theorem is illustrated using a simple mathematical example. Specific CPFs are then presented for particular problem formulations, and the method is applied to the optimal design and control of a micro-electrical mechanical system actuator.


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