PMID- 31936635
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200928
IS  - 2072-666X (Print)
IS  - 2072-666X (Electronic)
IS  - 2072-666X (Linking)
VI  - 11
IP  - 1
DP  - 2020 Jan 9
TI  - A Design Methodology of Digital Control System for MEMS Gyroscope Based on 
      Multi-Objective Parameter Optimization.
LID - 10.3390/mi11010075 [doi]
LID - 75
AB  - This paper presents a novel multi-objective parameter optimization method based 
      on the genetic algorithm (GA) and adaptive moment estimation (Adam) algorithm for 
      the design of a closed-loop control system for the sense mode of a 
      Microelectromechanical systems (MEMS) gyroscope. The proposed method can improve 
      the immunity of the control system to fabrication tolerances and external noise. 
      The design procedure starts by deriving a parameterized model of the closed-loop 
      of the sense mode. The loop parameters are then optimized by the GA. Finally, the 
      ensemble of optimized loop parameters is tested by Monte Carlo analysis to obtain 
      a robust optimal solution. Simultaneously, the Adam-least mean square (LMS) 
      demodulator, which is appropriate for the demodulation of very noisy signals, is 
      also presented. Compared with the traditional method, the time consumption of the 
      design process is reduced significantly. The digital control system is 
      implemented by the print circuit board based on embedded Field Programmable Gate 
      Array (FPGA). The experimental results show that the optimized control loop has 
      achieved a better performance, the system bandwidth in open-loop and optimal 
      closed-loop control system is about 23 Hz and 101 Hz, respectively. Compared to a 
      non-optimized closed-loop system, the bias instability reduced from 0.0015 degrees /s to 
      7.52 x 10(-4) degrees /s, the scale factor increased from 17.7 mV/( degrees /s) to 23 mV/( degrees /s) 
      and the non-linearity of the scale factor reduced from 0.008452% to 0.006156%.
FAU - Gu, Haoyu
AU  - Gu H
AD  - Institute of Electronic Engineering, China Academy of Engineering Physics, 
      Mianyang 621999, China.
FAU - Su, Wei
AU  - Su W
AD  - Institute of Electronic Engineering, China Academy of Engineering Physics, 
      Mianyang 621999, China.
FAU - Zhao, Baolin
AU  - Zhao B
AD  - Institute of Electronic Engineering, China Academy of Engineering Physics, 
      Mianyang 621999, China.
FAU - Zhou, Hao
AU  - Zhou H
AD  - Institute of Electronic Engineering, China Academy of Engineering Physics, 
      Mianyang 621999, China.
FAU - Liu, Xianxue
AU  - Liu X
AD  - Institute of Electronic Engineering, China Academy of Engineering Physics, 
      Mianyang 621999, China.
LA  - eng
PT  - Journal Article
DEP - 20200109
PL  - Switzerland
TA  - Micromachines (Basel)
JT  - Micromachines
JID - 101640903
PMC - PMC7019554
OTO - NOTNLM
OT  - Adam-LMSD algorithm
OT  - MEMS gyroscope
OT  - Monte Carlo analysis
OT  - closed-loop system
OT  - genetic algorithm
COIS- The authors declare no conflict of interest.
EDAT- 2020/01/16 06:00
MHDA- 2020/01/16 06:01
PMCR- 2020/01/09
CRDT- 2020/01/16 06:00
PHST- 2019/12/14 00:00 [received]
PHST- 2020/01/07 00:00 [revised]
PHST- 2020/01/08 00:00 [accepted]
PHST- 2020/01/16 06:00 [entrez]
PHST- 2020/01/16 06:00 [pubmed]
PHST- 2020/01/16 06:01 [medline]
PHST- 2020/01/09 00:00 [pmc-release]
AID - mi11010075 [pii]
AID - micromachines-11-00075 [pii]
AID - 10.3390/mi11010075 [doi]
PST - epublish
SO  - Micromachines (Basel). 2020 Jan 9;11(1):75. doi: 10.3390/mi11010075.