Device robust-design is inherently a multiple-objective optimization problem.Using design of experiments (DoE) combined with response surface methodology (RSM) can satisfy the great incentive to reduce the number of t...Device robust-design is inherently a multiple-objective optimization problem.Using design of experiments (DoE) combined with response surface methodology (RSM) can satisfy the great incentive to reduce the number of technology CAD(TCAD) simulations that need to be performed.However,the errors of RSM models might be large enough to diminish the validity of the results for some nonlinear problems.To find the feasible design space,a new method with objectives-oriented design in generations that takes the errors of RSM model into account is presented.After the augment design of experiments in promising space according to the results of RSM model in current generation,the feasible space will be emerging as the model errors deceasing.The results on FIBMOS examples show that the methodology is efficient.展开更多
针对光伏系统输出功率受环境影响而呈现的非线性时变特性,以及难以稳定跟踪最大功率点(maximum power point,MPP)的问题,提出一种基于粒子群优化算法(particle swarm optimization,PSO)来优化收敛因子的光伏最大功率鲁棒控制器设计方法...针对光伏系统输出功率受环境影响而呈现的非线性时变特性,以及难以稳定跟踪最大功率点(maximum power point,MPP)的问题,提出一种基于粒子群优化算法(particle swarm optimization,PSO)来优化收敛因子的光伏最大功率鲁棒控制器设计方法。通过建立光伏阵列数学模型,引入自适应调整的学习因子与惯性权重以优化PSO算法,从而增强其全局搜索能力。同时,结合鲁棒控制理论构建H∞控制器以抑制外部扰动,并通过线性矩阵不等式配置系统极点以提升鲁棒性。实验结果表明,在局部遮挡条件下,该方法能够在0.25秒内快速跟踪到MPP,电压稳定在328 V,并且在干扰后状态变量能够迅速恢复稳定,震荡幅度降低约40%。该控制器显著提升了光伏系统在复杂环境下的动态响应与抗干扰能力,为高效、稳定的光伏发电运行提供了可靠的解决方案。展开更多
文摘Device robust-design is inherently a multiple-objective optimization problem.Using design of experiments (DoE) combined with response surface methodology (RSM) can satisfy the great incentive to reduce the number of technology CAD(TCAD) simulations that need to be performed.However,the errors of RSM models might be large enough to diminish the validity of the results for some nonlinear problems.To find the feasible design space,a new method with objectives-oriented design in generations that takes the errors of RSM model into account is presented.After the augment design of experiments in promising space according to the results of RSM model in current generation,the feasible space will be emerging as the model errors deceasing.The results on FIBMOS examples show that the methodology is efficient.
