Abstract
This paper proposes a Kriging assisted covariance matrix adaptation evolution strategy (AK-CMA-ES) for optimization of mechatronics device structures. The objective of the proposed method is to design reliable structures with reduced computational cost of the multiphysics finite element simulation. The Finite element model intends to analyze the sequence of failure events in mechatronic devices. This numerical model is used to estimate the thermal cycles to failure. Subsequently, the AK-CMA-ES optimization process is performed in order to improve the performance of structural design of mechatronic systems and to find the best designs with safety and reasonable computational costs. The proposed method couple the kriging metamodel with the covariance matrix adaptation evolution strategy (CMA-ES). Kriging metamodel is used to replace the finite element simulation in order to overcome the computational cost of finite element model simulation. Kriging is used together with CMA-ES and sequentially updated and its quality is measured according to its ability in the ranking of the population through approximate ranking procedure (ARP). The application of this method in the optimization of mechatronic systems proves its efficiency and ability to improve the performance of mechatronic systems with avoiding the problem of tedious computation.
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