LMI–based robust controller design approach in aircraft multidisciplinary design optimization problem

In order to improve the performance of automotive product platforms and product families while keeping high development efficiency, a product family optimization design method that combines shared variable decision-making and multidisciplinary design optimization (MDO) is proposed. First, the basic concepts related to product family design optimization were clarified. Then, the mathematical description and MDO model of the product family optimization problem were established, and the improved product family design process was given. Finally, for the chassis product family optimization problem of an automotive product platform, the effectiveness of the proposed optimization method, and design process were exemplified. The results show that the collaboratively optimized product family can effectively handle the coordination between multiple products and multiple targets, compared to Non-platform development, it can maximize the generalization rate of vehicle parts and components under the premise of ensuring key performance, and give full play to the advantages of product platforms.

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A robust controller design approach for systems with distributed time-delay

2014 European Control Conference (ECC) ◽

10.1109/ecc.2014.6862323 ◽

2014 ◽

Cited By ~ 2

Author(s):

Altug Iftar

Keyword(s):

Time Delay ◽

Controller Design ◽

Design Approach ◽

Robust Controller ◽

Distributed Time Delay ◽

Robust Controller Design

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A Regularized Inexact Penalty Decomposition Algorithm for Multidisciplinary Design Optimization Problem With Complementarity Constraints

Volume 5: 35th Design Automation Conference, Parts A and B ◽

10.1115/detc2009-87278 ◽

2009 ◽

Author(s):

Shen Lu ◽

Harrison M. Kim

Keyword(s):

Design Optimization ◽

Multidisciplinary Design Optimization ◽

Optimization Problem ◽

Original Problem ◽

Equilibrium Problems ◽

Decomposition Algorithm ◽

Multidisciplinary Design ◽

Stationary Points ◽

Complementarity Constraints ◽

Regularization Technique

Economic and physical considerations often lead to equilibrium problems in multidisciplinary design optimization (MDO), which can be captured by MDO problems with complementarity constraints (MDO-CC) — a newly emerging class of problem. Due to the ill-posedness associated with the complementarity constraints, many existing MDO methods may have numerical difficulties solving the MDO-CC. In this paper, we propose a new decomposition algorithm for MDO-CC based on the regularization technique and inexact penalty decomposition. The algorithm is presented such that existing proofs can be extended, under certain assumptions, to show that it converges to stationary points of the original problem and that it converges locally at a superlinear rate. Numerical computation with an engineering design example and several analytical example problems shows promising results with convergence to the all-in-one (AIO) solution.

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