基于克里金模型的微电热驱动器优化设计

基于局部型四维参数的函数，采用克里金代理模型和遗传-粒子群（GA-PSO）优化算法，开展大位移U型电热驱动器优化设计研究. 建立U型电热驱动器的多物理场仿真模型并进行实验验证. 发现在不同电压下，电热驱动器仿真位移与实验位移曲线一致，从而保证克里金模型中样本数据来源的可靠性. 搭建ANSYS和MATLAB联合自动仿真平台以解决克里金模型中样本数据的批量采集问题. 基于该平台，采用简单随机抽样的方法，得到不同采样点下电热驱动器的位移，从而形成样本数据. 根据样本数据建立克里金模型并基于该模型采用遗传-粒子群算法进行参数优化. 研究结果表明，克里金模型能代替有限元模型准确预测驱动器的位移；控制驱动器形状的4个关键参数与位移成单调关系；经形状优化后，18 V电压下U型电热驱动器的位移提高35.2%.

Optimization and design of micro-electro-thermal actuator based on Kriging model

A combination of the Kriging surrogate model and the genetic and particle swarm optimization (GA-PSO) algorithm was applied to the design and optimization of the U-shaped electro-thermal actuator with large displacement, based on the local function with four parameters. The multi-physical coupling simulation model of the U-shaped electro-thermal actuator was established and validated by experiment. The displacement from simulation shows a good agreement with that from experiment with different voltages, which ensures the accuracy of the sample data for the Kriging model. A co-simulation using ANSYS and MATLAB was created, which can capture the sample data in batches. The simple random sampling was utilized to get sample points. The displacements of different sample points were obtained as sample data. The Kriging model was established with the sample data and the GA-PSO algorithm was used for optimization based on the established Kriging model. Results show that the Kriging model can replace the simulation model for predicting the displacement of the U-shaped actuator precisely. The monotonic relationship exists between the displacement and each of the four key parameters, which can decide the shape of the actuator. The displacement of the U-shaped actuator increases 35.2% under 18 V after the shape optimization.