摘要
针对单目标遗传算法设计优化高阶Σ-Δ微机电系统(Σ-ΔMEMS)加速度计时易出现的稳定性问题,提出了基于多目标遗传算法的MEMS加速度计环路滤波器优化设计方法。对三阶非限定性Σ-ΔMEMS加速度计系统,采用多目标遗传算法,将∞—范数和信噪比作为设计目标对其环路滤波器参数进行优化设计。结果表明:相比只针对信噪比进行优化的传统单目标遗传算法,多目标遗传算法在确保高信噪比的同时,提高了系统的相位裕度,使得最大稳定输入信号范围增幅超过1倍,增强了系统对MEMS敏感元件工艺误差的鲁棒性。
To address the stability problem which occurs in high-order ∑-△ micro-electro-mechanical system （MEMS） accelerometer design using single-objective genetic algorithm,a MEMS aeeelerometer loop filter optimal design methodology based on multi-objective genetic algorithm （MOGA） is proposed. For 3rd-order non-finite ∑-△ MEMS aecelerometer system, MOGA is adopted ,loop filter parameters are designed and optimized using both signal to noise ratio（SNR） and infinity norm as design targets. Compared to single-objective genetic algorithm which optimize only for SNR, MOGA improves phase margin significantly, double the maximum stable input signal range, and enhance system robustness to technique error of MEMS sensitive element, under the premise of high SNR.
作者
王梦醒
刘丹
熊兴崟
李宗伟
韩可都
WANG Meng-xing;LIU Dan;XIONG Xing-yin;LI Zong-wei;HAN Ke-du(Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China;University of Chinese Academy of Sciences, Beijing 100049, China)
出处
《传感器与微系统》
CSCD
2018年第5期64-66,69,共4页
Transducer and Microsystem Technologies
基金
中国科学院A类战略性先导科技专项项目(XDA14040102)
国家科技重大专项项目(2017ZX05008-008-021)
关键词
微机电系统
多目标遗传算法
稳定性
环路滤波器
micro-electro-mechanical system （ MEMS ）
multi-objective genetic algorithm （ MOGA ）
stability
loop filter
