Simulator for studies of fuzzy control methods

Hayashi, Ken’ichiro; Otsubo, Akifumi

doi:10.1016/s0165-0114(96)00196-0

Cited by 11 publications

(7 citation statements)

References 6 publications

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“…Because the movement rate of EOF is proportional to the electric field, the flow speed can be controlled by changing the intensity of the electric field. At the control rule, the fuzzy logic was used to calculate the optimal relationship between the distance and applied voltage [ 8 , 9 ].…”

Section: Methods and Equipmentsmentioning

confidence: 99%

Development of an Integrated Chip for Automatic Tracking and Positioning Manipulation for Single Cell Lysis

Young¹,

Hsieh²,

Ay³

2012

Sensors

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This study adopted a microelectromechanical fabrication process to design a chip integrated with electroosmotic flow and dielectrophoresis force for single cell lysis. Human histiocytic lymphoma U937 cells were driven rapidly by electroosmotic flow and precisely moved to a specific area for cell lysis. By varying the frequency of AC power, 15 V AC at 1 MHz of frequency configuration achieved 100% cell lysing at the specific area. The integrated chip could successfully manipulate single cells to a specific position and lysis. The overall successful rate of cell tracking, positioning, and cell lysis is 80%. The average speed of cell driving was 17.74 μm/s. This technique will be developed for DNA extraction in biomolecular detection. It can simplify pre-treatment procedures for biotechnological analysis of samples.

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Section: Methods and Equipmentsmentioning

confidence: 99%

Development of an Integrated Chip for Automatic Tracking and Positioning Manipulation for Single Cell Lysis

Young¹,

Hsieh²,

Ay³

2012

Sensors

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show abstract

“…The inference rules are constructed in a fuzzy rule base. The settings of the fuzzy rules have often led to tedious and time-consuming trial design procedures [30,31]. Such taxing procedures are caused by the incomplete linguistic descriptions of relationships by experts, as they are limited by time.…”

Section: Fuzzy Inference System and Mamdani Typementioning

confidence: 99%

Fuzzy intelligent inference scheme for self-health estimation via blood pressure and body mass index in out-of-hospital

Yang

Huang

Chang

et al. 2015

Journal of Intelligent &Amp; Fuzzy Systems

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E-health for both chronic patients and wellness persons has recently attracted the interest of researchers and practitioners. The physical vital signs are one of the most important factors used to evaluate individual wellness. The variations of daily vital signs are even significant in analyzing physical health trends that can be applied in self-caring for individuals at home. In this paper, an Intelligent-Mamdani Inference Scheme (IMIS) based on fuzzy markup language (FML) is proposed to define approximate health conditions of the individuals via the blood pressure and the body mass index in out-of-hospital. The IMIS can fuse these vital signs and infer semantic health summary using the constructed fuzzy rules and the knowledge base. The main contributions of the this paper are: (1) to leverage personal vital signs by fuzzy logic technology for self-health management at home; (2) to design the novel scheme in detail for practicability and reproduction. The experimental results show that the scheme is feasible to infer personal health status. An individual can easily recognize self-health trend through semantic sentence generation, which further advances self-health management in out-of-hospital.

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“…The simulation results verified the effectiveness of the proposed control algorithm. In [5] a design method of Fuzzy control systems depending on trial and error has been presented, and effective and convenient support tools for the study and design of Fuzzy control systems have been introduced. A self learning Fuzzy logic system for (MIMO) plants has been introduced [6], where a plant model is not required for training.…”

Section: Design Of Model Reference Adaptive Controllermentioning

confidence: 99%