Two-objective metaheuristic optimization for floating gate transistor-based CMOS-MEMS inertial sensors

B. Granados-Rojas, M. A. Reyes-Barranca, Y. E. González-Navarro, G. S. Abarca-Jiménez, M. A. Alemán-Arce, S. Mendoza-Acevedo, L. M. Flores-Nava

Research output: Contribution to journalArticlepeer-review

Abstract

In this work, a study case is presented in which the design of the layout for a CMOS sensor cell is partially automated by implementing a metaheuristic algorithm to find the best tradeoff between two conflicting objectives (two quantitative opposite and not totally independent yet desired performance or design qualities) among the set of feasible layout and electronic device configurations within a constricted search space. The feasibility of a solution (a particular configuration) and its capability to fulfill every requested objective, is determined by its compliance to the CMOS-MEMS design rules and fabrication process. Any given solution besides showing optimal or very near-to-the-optimal characteristics, must be suitable to be fabricated in the CMOS conventional process which for this case is a 0.5μm, 3-metal 2-poly N-well fabrication, beside this, since monolithic inertial sensors generally contains embedded movable electromechanical parts a surface micromachining must be considered. Simulation data and behavior of the bio-inspired metaheuristic algorithm used during the design process are presented, as well as electromechanical simulation results based the automatic-generated solutions.

Original languageEnglish
JournalMicrosystem Technologies
DOIs
StateAccepted/In press - 2021

Keywords

  • CMOS-MEMS
  • FGMOS
  • Floating-gate
  • Genetic algorithm
  • MEMS
  • Optimization

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