An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator
COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the devel...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Actuators |
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| Online Access: | https://www.mdpi.com/2076-0825/10/3/51 |
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| author | Jozef Živčák Michal Kelemen Ivan Virgala Peter Marcinko Peter Tuleja Marek Sukop Ján Liguš Jana Ligušová |
| author_facet | Jozef Živčák Michal Kelemen Ivan Virgala Peter Marcinko Peter Tuleja Marek Sukop Ján Liguš Jana Ligušová |
| author_sort | Jozef Živčák |
| collection | DOAJ |
| description | COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes. |
| first_indexed | 2024-03-09T05:14:38Z |
| format | Article |
| id | doaj.art-04b31243f9fa43a9a209297676ca42c5 |
| institution | Directory Open Access Journal |
| issn | 2076-0825 |
| language | English |
| last_indexed | 2024-03-09T05:14:38Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Actuators |
| spelling | doaj.art-04b31243f9fa43a9a209297676ca42c52023-12-03T12:46:38ZengMDPI AGActuators2076-08252021-03-011035110.3390/act10030051An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical VentilatorJozef Živčák0Michal Kelemen1Ivan Virgala2Peter Marcinko3Peter Tuleja4Marek Sukop5Ján Liguš6Jana Ligušová7Department of Biomedical Engineering and Measurement, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Mechatronics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Mechatronics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Production Systems and Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Production Systems and Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, SlovakiaDepartment of Production Systems and Robotics, Faculty of Mechanical Engineering, Technical University of Košice, 04200 Košice, SlovakiaKYBERNETES, s.r.o., Omská 14, 04001 Košice, SlovakiaKYBERNETES, s.r.o., Omská 14, 04001 Košice, SlovakiaCOVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.https://www.mdpi.com/2076-0825/10/3/51AmbuBagANFISartificial lung ventilationcoronavirusCOVID-19neuro-fuzzy |
| spellingShingle | Jozef Živčák Michal Kelemen Ivan Virgala Peter Marcinko Peter Tuleja Marek Sukop Ján Liguš Jana Ligušová An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator Actuators AmbuBag ANFIS artificial lung ventilation coronavirus COVID-19 neuro-fuzzy |
| title | An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator |
| title_full | An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator |
| title_fullStr | An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator |
| title_full_unstemmed | An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator |
| title_short | An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator |
| title_sort | adaptive neuro fuzzy control of pneumatic mechanical ventilator |
| topic | AmbuBag ANFIS artificial lung ventilation coronavirus COVID-19 neuro-fuzzy |
| url | https://www.mdpi.com/2076-0825/10/3/51 |
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