Journal of Intelligent Material Systems and Structures · 2007 · 24 citations · 25 references
EngineeringMechanical EngineeringActuatorsDesign OptimizationOptimizationActuator DesignEvolutionary ComputationGenetic AlgorithmsPiezoelectric ActuatorsVibration AnalysisVibration ControlConfiguration OptimizationFin DesignFinite Element ModelingFrequency Response Function AnalysisGenetic Algorithm Based DesignGenetic Algorithm OptimizationPiezoelectric Actuator ModelingPiezoelectric Effect
This study presents a novel approach to optimizing the configuration of piezoelectric actuators for vibration control of a flexible aircraft fin. The fitness (cost) function for optimization using a genetic algorithm is derived directly from the frequency response function (FRF) obtained from a finite element model of the fin. In comparison to existing approaches, this method allows optimization on much more complex geometries where the derivation of an analytical fitness function is prohibitive or impossible. This technique is applied to two optimization problems for vibration control of the fin. First, the position of a single actuator is optimized anywhere within a judiciously pre-determined area of the fin using a genetic algorithm for polynomial surface fitting of the FRF in order to obtain a continuous fitness function. Next, the configuration of a pre-determined number of up to 48 separate actuators is optimized within the same area. The optimization approach is verified against experimental results obtained from a set of 12 actuators fixed to an experimental model of the fin.
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Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations
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Optimization, and Machine Learning
D. E. Goldberg · Medical Entomology and Zoology · 1989 · 599 citations