2024-03-29T16:18:46+03:30 http://joc.kntu.ac.ir/browse.php?mag_id=53&slc_lang=fa&sid=1
53-832 2024-03-29 10.1002
Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Evaluation of Lung Involvement in Patients with Coronavirus Disease from Chest CT Images Using Multi-Objective Self-Adaptive Differential Evolution Approach Ali Karsaz karsaz@khorasan.ac.ir Under the global pandemic of COVID-19 over the last year, the use of image processing techniques and the artificial intelligence algorithms to analysis chest X-ray (CXR) images is becoming important. Determining the lung involvement and percentage development of COVID-19 is one of most important requirements for the hospitalization centers. The most studies in this field belong to the articles based on the deep learning methodologies using convolution neural networks, which are usually implemented to facilitate the screening process. Only a few number of studies are about the determining the percentage of lung involvement and development of coronavirus based on CXR images. The lack of comprehensive datasets of CT images with a large amount of samples is one of the most important issues in this field. Determining of lung infection in COVID-19 patients, based on different CXR images in different days, has its own challenges such as different image sizes, illumination density, radiation dose of X-ray and angle of radiation, which makes it impossible to the implement a simple differential filter on two different images. Using an optimization self-adaptive algorithm with differential and multi-objective approach can improve the performance accuracy with a corresponding reduction in computation time. COVID-19 lung involvement chest X-ray images image processing multi-objective self-adaptive differential evolution algorithm. 2021 2 01 1 14 http://joc.kntu.ac.ir/article-1-832-en.pdf 10.52547/joc.14.5.1
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Prediction of the spread of Corona-virus carrying droplets in a metro wagon - A computational based artificial intelligence approach Javad Mohebbi Najm Abad javad.mohebi@gmail.com Rasool Alizadeh rasoolalizadeh86@gmail.com Mehrdad Mesgarpour mesgarpour-mehrdad@hotmail.com Assessing the risk of transmitting the coronavirus is essential for protecting public health under the COVID-19 epidemic. Public transportation such as buses and metro wagon is the most important COVID-19 dispersion source. In the last decade, numerical simulation plays a vital role in predicting. In this case study, a combination of numerical simulation and artificial intelligence tries to predict the droplet of the sneezing process. As a case study, the Metro wagon was considered, and droplet dispersion along the bus was studied. The result indicated that the small diameter could easily transport along with the wagon. It also shows that the large area under affected by particle deposition. In this case study, a combination of numerical simulation and artificial intelligence has a great result. COVID-19 Droplet distribution CFD Artificial intelligent 2021 2 01 15 22 http://joc.kntu.ac.ir/article-1-822-en.pdf 10.52547/joc.14.5.15
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Study of Knowledge, Attitude and Practice of citizen of Isfahan towards Using Electronic Services during the Corona Outbreak (COVID-19) Mojgaan Bahrami m.bahrami@hashtbehesht.ac.ir Vida Shamaei vadashamaei1368@gmail.com The present study examined the level of knowledge, attitude, and practice of the people of Isfahan in the field of using electronic services during the corona outbreak. Methods: The research was applied in terms of purpose and descriptive-correlational nature and was conducted on 384 people over 18 years old living in Isfahan. The tool was a researcher-made questionnaire consisting of 35 questions that were distributed among eligible people by snowball sampling method. . Data were analyzed by SPSS and Smart PLS software.   Results: The knowledge, attitude, and practice of the studied individuals in the field of using electronic services during the corona outbreak are significantly different from the average and is higher than the average. This rate was 3.99 for knowledge, 4.11 for attitude and 3.75 for performance. There is a difference between women and men in the level of knowledge and attitude in the use of electronic services and it is more in men, but there is no significant difference between the performance of women and men in the use of electronic services. The level of knowledge and practice does not differ based on education. The attainment of people with Ph.D. education is stronger in the field of using electronic services. Also, there is a significant difference between the variables of knowledge, attitude and practice of Isfahan people in using electronic services based on job and there is more difference in faculty members. And are in the ages of 30 to 50 years old. Conclusion: The results show that the knowledge, attitude and practice of the citizens of Isfahan in the use of electronic services are higher than average. The launch of various electronic service delivery systems in many organizations, organizations and commercial businesses and stores has enabled the citizens of Isfahan to receive various services provided by these organizations at home and through mobile or computer systems. During the COVID-19. pandemic, there is less need to be physically present in public places... Awareness in the use of electronic services attitude in the use of electronic services performance in the use of electronic services COVID-19 2021 2 01 23 31 http://joc.kntu.ac.ir/article-1-801-en.pdf 10.52547/joc.14.5.23
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Investigation of the smoking prevalence among critically ill patients with COVID-19 Sina Bagheri Nezhad s_bagherinezhad@comp.iust.ac.ir Elham Abdi e_abdi@metaleng.iust.ac.ir Nasser Mozayani mozayani@iust.ac.ir Marzieh Mehrafza dr.mehrafza@yahoo.Com In this paper, we investigate the prevalence rate of smoking in COVID-19 patients and examine whether there is a difference in the distribution of smokers between the two statistical populations of critically ill COVID-19 patients and the entire Iranian population or not. To do this, we first prepared a sample of 300 COVID-19 patients admitted to hospitals in Tehran and Rasht. Then, through the non-parametric statistical runs test, we show that the sample was randomly selected and it is possible to generalize the result of tests on the sample to the community of hospitalized COVID-19 patients. In continuation, we examined the hypothesis that the prevalence of smoking among COVID-19 patients admitted to hospitals is equal to the prevalence rate of smoking in the whole Iranian society. For this purpose, we used the non-parametric chi-square test and it was observed that this hypothesis is rejected. The data show that there is a significant difference in the prevalence of smoking between critically ill COVID-19 patients and the whole of Iranian society. Also, it can be concluded that, the prevalence rate of smoking among COVID-19 hospitalized patients is lower than this rate in the whole Iranian society. The above results show the need for serious research in this field and confirm that while avoiding any positive or negative tendency towards smoking, the causes and factors affecting this phenomenon should be investigated and drugs can be prepared and produced accordingly. smoking COVID-19 coronavirus statistical hypothesis testing runs test chi-square test 2021 2 01 33 37 http://joc.kntu.ac.ir/article-1-816-en.pdf 10.52547/joc.14.5.33
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 The effect of temperature on the binding affinity of Remdesivir and RdRp enzyme of SARS-COV-2 virus using steered molecular dynamics simulation Mohadese Abidi m.90abidi@yahoo.com Reza Soheilifard r.soheilifard@hsu.ac.ir Reza Hasanzadeh Ghasemi r.hasanzadeh@hsu.ac.ir The fatal SARS-COV-2 virus appeared in China at the end of 2019 for the first time. This virus has similar sequence with SARS-COV in 2002, but its infection is very high rate. On the other hand, SARS-COV-2 is a RNA virus and requires RNA-dependent RNA polymerase (RdRp) to transcribe its viral genome. Due to the availability of the active site of this enzyme, an effective treatment is targeting it to inhibit SARS-COV-2 reproduction. Remdesivir is an inhibitor for Hepatitis C and Ebola that is approved by Food and Drug Administration. Also, it has shown good results in inhibition of main protease and RdRp enzyme of SARS-COV-2. In this paper, the inhibitory of Remdesivir in various temperatures has been observed using steered molecular dynamics simulation. For this reason, the binding affinity of Remdesivir and RdRp were evaluated by molecular docking at four different temperatures (from 17 to 47 °C). According to the results, the rupture force and pulling work to separate the Remdesivir from RdRp decrease with increasing temperature. It is also shown that at higher temperatures, Gibbs free energy is reduced due to its relation with pulling work. SARS-COV-2 RNA-dependent RNA polymerase Molecular Docking Steered Molecular Dynamics Simulation Remdesivir 2021 2 01 39 47 http://joc.kntu.ac.ir/article-1-815-en.pdf 10.52547/joc.14.5.39
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Modeling of self-assessment system of COVID-19 disease diagnosis using Type-2 Sugeno fuzzy inference system Maryam Kamarzarrin maryam.kamarzarrin@gmail.com najmeh eghbal najmeh.eghbql@sadjad.ac.ir Due to the continuation of the pandemic of Coronavirus in the whole world, the number of deaths has reached over one million, based on the World Health Organization reports. Early diagnosis of the illness can be a great assistance in order to break the chain of disease transmission. Nowadays, COVID-19 test kits are so limited in numbers, and expensive in terms of a cost, which slows down the diagnosis procedure and makes it difficult, thus, it is necessary to diagnose the disease in the early stages, to prevent its incidence. Therefore, we decided to propose a self-assessment method for COVID-19 disease, using a type-2 Sugeno fuzzy inference system, which causes conservation in time and costs. The system is prepared based on 98 rules, according to the World Health Organization instructions, using MATLAB software to simulate and diagnose the disease. The results show that Sugeno fuzzy with better correlation coefficient R^2=0.94 and error squared RMSE = 0.045, respectively, has acceptable accuracy for estimating and identifying COVID-19 disease. The self-assessment consequences are very promising and can prevent the further spread of the disease. COVID-19 Type-2 Fuzzy Logic Sugeno fuzzy inference system self-assessment. 2021 2 01 49 57 http://joc.kntu.ac.ir/article-1-817-en.pdf 10.52547/joc.14.5.49
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Fuzzy Sliding Mode Controller Design and Analysis of an SQEIAR Epidemic Model for COVID-19 to Determine the Quarantine Rate Amir Hossein Amiri Mehra a.amirimehra@grad.kashanu.ac.ir Mohsen Shafieirad m.shafieirad@kashanu.ac.ir Zohreh Abbasi abbasi.z@grad.kashanu.ac.ir Iman Zamani zamaniiman@shahed.ac.ir Zohreh Aarabi aarabizohreh.academic@gmail.com According to the global prevalence of coronavirus (COVID-19) pandemic, mathematical models can predict and control the dynamic behavior of the pandemic. Therefore, in this study, a comprehensive model is considered to examine the trend of COVID-19 based on Susceptible, Exposed, Infected (Symptomatic and Asymptomatic), and Recovered individuals. In the absence of a curative treatment or vaccination campaign, the group of "quarantined people" is added to the model. Then, a positivity analysis of states is examined, and the threshold criterion (R_0) is determined. The equilibrium points (disease-free and endemic) are also calculated, and their stability is investigated using the Jacobin matrix. The quarantine rate is regulated as the only control input using the fuzzy sliding mode controller. The efficiency of the controller is also investigated in the presence of uncertainty in model parameters. Also, the impact of the infected community on other communities, considering the controller, will be examined. Finally, the performance and efficiency of the proposed controller are evaluated. COVID-19 Mathematical Modeling Stability Analysis Quarantine Fuzzy Sliding Mode. 2021 2 01 59 70 http://joc.kntu.ac.ir/article-1-820-en.pdf 10.52547/joc.14.5.59
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Diagnosis of COVID-19 disease by fuzzy expert system designed based on input-output mohammad dehghandar m_dehghandar@pnu.ac.ir M.pabasteh@yahoo.com Emailtorazieh@gmail.com Accurate prediction and diagnosis of COVID-19 disease is very important for everyone, especially for medical professionals. On the other hand, the use of fuzzy systems in medicine is increasing rapidly. In this study, a fuzzy system was designed using the information of 375 patients suspected of having COVID-19 disease who referred to Imam Khomeini (Tehran), Alborz (Karaj) and Kowsar(Karaj) hospitals. For this purpose, 300 people were considered to extract the rules and 75 people were considered as test data. Information on 12 important parameters of COVID-19 disease including fever, cough, headache, gastrointestinal symptoms, skin rash, sense of smell and taste, underlying disease, chest CT, blood oxygen level, lethargy, age, family history and severity of COVID-19 disease received. The fuzzy expert system was designed with 29 rules after reviewing the rules and removing similar and contradictory rules by using their degree calculation. In this system, by integrating some factors, finally 8 input variables and one output variable were considered that was used by product inference engine, singleton fuzzifier and center average defuzzifier. It was observed that the designed fuzzy expert system provides very good results, so that it detects 93% of Covid-19 disease with high accuracy and also the sensitivity of the system is more than 95% and the specificity of the designed system is more than 87%. COVID-19 fuzzy expert input-output diagnose. 2021 2 01 71 78 http://joc.kntu.ac.ir/article-1-833-en.pdf 10.52547/joc.14.5.71
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Design and implementation of a model predictive controller for the COVID-19 spread restraint in Iran Mahdi Rezaei Bahrmand RezaeiMahdi2018@gmail.com Hamid Khaloozadeh h_khaloozadeh@kntu.ac.ir Parastoo Reihani Ardabili P_reihani@pnu.ac.ir In this paper, a model is proposed based on the different levels of social restrictions for the COVID-19 spread restraint in Iran. Also, a Genetic Algorithm (GA) identifies parameters of model using reported main data from the Iranian Ministry of Health and simulated data based on proposed model. Whereas Model Predictive Control (MPC) is a popular method which has been widely used in process control, after the discretization of model by a common method like Euler method, then we can consider the appropriate constraints and solve online optimization problem. In this paper, we have shown that the MPC controller able to flatten infected (symptomatic) individual curve and decrease its peak by applying the different levels of social restrictions. Numerical example and simulation results, based on main data, are given to illustrate the capability of this method. Model Predictive Control System identification GA algorithm COVID-19. 2021 2 01 79 88 http://joc.kntu.ac.ir/article-1-837-en.pdf 10.52547/joc.14.5.79
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Modeling and analysis of the spread of the COVID-19 pandemic using the classical SIR model Zahra Zare zarezahra.3981@gmail.com Nastarn Vasegh N.vasegh@sru.ac.ir In this paper modeling, analysis and prediction of novel epidemic of COVID-19 are concerned to identify effective spread parameters of it in Iran. For this purpose, the basic susceptible-infected-removed (SIR) model is used which has two parameters: the infection rate and remove rate. Because of several maximum points in the Iranian data and the single peak of the SIR model, it is not possible to use a model with the same parameters for all times. For this reason, the Iranian data is divided into five time periods and then the parameters of each period are obtained. In addition to adapting to the behavior of disease-related data, these time periods are consistent with the realities of society, including the timing of government decisions and the changing patterns of individuals in society. Finally, an analysis based on the obtained parameters and the trend of disease spread in the continuation of this year is presented. Since the economic, social and health consequences of this virus are catastrophic, using the results of mathematical modeling to identify the factors affecting the spread of the disease can be a step towards future actions to control the disease. COVID-19 SIR classic model epidemic reproduction number. 2021 2 01 89 96 http://joc.kntu.ac.ir/article-1-821-en.pdf 10.52547/joc.14.5.89
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Developed Technologies and Active Startup Companies in Dealing with COVID-19 Pandemic in Iran Bijan Moaveni b.moaveni@kntu.ac.ir On February 2020, Iran reported its first confirmed cases of infections COVID-19 pandemic and since than its effects have been widely spread across in Iran and worldwide. The devastating consequences of the COVID-19 pandemic showed that science and technologies play an important role in ensuring national security and social stability is such crises and we must learn from this event to better prepare for similar cases. In this paper, we will review the developed technologies in Iran to deal with the COVID-19 pandemic. We tried to gather the information of the startup companies and their presented technologies across Iran. After validating the gathered information, the startup companies have been classified based on their fields and their geographical locations. COVID-19 technology startup company dealing with COVID-19 pandemic. 2021 2 01 97 105 http://joc.kntu.ac.ir/article-1-831-en.pdf 10.52547/joc.14.5.97
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Analysis of the effects of COVID-19 virus on the Import, export and labor in Iran using system dynamic approach Nasser Safaie nsafaie@kntu.ac.ir Nafise ghazavi nghazavi9053@gmail.com ava sarabadani A.sarabdani96@yahoo.com Seyed amir NASRI S.A.Nasri74@gmail.com The new coronavirus (COVID-19) is caused by the acute respiratory syndrome 2. The disease was first diagnosed in December 2019 in Hubei Province, Wuhan City, China. On March 11, the World Health Organization declared the virus an epidemic. Until Mid-February, 2021, about 112 million people worldwide have been infected with the virus, of which about 2.500.000 people have lost their lives, according to the latest global statistics from the Worldometer database. The economic shock of the coronavirus outbreak has also led to negative economic impacts, including declining sales of many related businesses. In this paper, the effects of coronavirus on the Iranian economy are examined with a systems dynamics approach. First, the relationships of important variables affecting GDP in SPSS software are obtained and then the data is analyzed using Vensim software. In the following, by analyzing the sensitivity and providing recommendations, the impact of managerial insights to control the conditions of this new crisis will be examined. The results show that the correct use of the mask and the observance of social distance as well as air flow in spaces and avoidance of closed spaces have a significant effect on reducing the spread of this disease and reducing mortality. Coronavirus Economics Systems dynamics GDP Pandemic COVID -19. 2021 2 01 107 120 http://joc.kntu.ac.ir/article-1-824-en.pdf 10.52547/joc.14.5.107
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 A Review on Applications of Haptic Systems, Virtual Reality, and Artificial Intelligence in Medical Training in COVID-19 Pandemic Reza Heidari reza.heidari2060@gmail.com Mohammad Motaharifar md.motaharifar@gmail.com Hamidreza Taghirad taghirad@kntu.ac.ir Seyed-Farzad Mohammadi sfmohammadi@tums.ac.ir Alireza Lashay lashay@tums.ac.ir This paper presents a survey on haptic technology, virtual reality, and artificial intelligence applications in medical training during the COVID-19 pandemic. Over the last few decades, there has been a great deal of interest in using new technologies to establish capable approaches for medical training purposes. These methods are intended to minimize surgery's adverse effects, mostly when done by an inexperienced surgeon. Due to the world's unique situation during the pandemic, which causes several cities to be locked up, these methodologies are becoming more critical. They eliminate the physical contact requirement between medical personnel and fellows, which decreases the risk of being infected with the virus. This study aims to present new applications for haptic technology, virtual reality, artificial intelligence, and new fields where they can provide a viable solution in the COVID-19 pandemic or any other similar crises. haptic systems medical training artificial intelligence virtual reality COVID-19. 2021 2 01 121 125 http://joc.kntu.ac.ir/article-1-819-en.pdf 10.52547/joc.14.5.121
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Dynamic model of COVID-19 disease and performance analysis of Iran, Germany and Turkey with experimental data mohammad maghsoudi Dr.MohammadMaghsoudi@gmail.com mehdi siahi mehdi.siahi@srbiau.a.ir Covid-19 disease is caused by a new type of coronavirus, which is an infectious disease that has so far infected more than 90 million people and killed about 2 million. Hygiene programs, treatment, education, restrictions and other preventive measures are the inputs that can limit the spread of the disease, which in turn reduces the incidence of the disease. In this paper, in order to investigate some of the influential parameters, a nonlinear model is analyzed to investigate the effect of hygiene and education on the transmission dynamics of Covid-19 disease. Stability analysis and equilibrium points are examined to determine the generation number (R0), the number that determines whether the disease disappears or not. The first part of the results shows that proper education and hygiene will reduce the number of patients. Also, in the second part of the results, the experimental data of three countries, Iran, Germany and Turkey from the beginning of the outbreak until January 10th, are examined and statistically compared. Then, the performance of these three countries at the peak of the disease outbreak (November, December and January) is analyzed. The results show that Iran has performed relatively better, despite sanctions and a lack of facilities, especially in the last three months. COVID-19 (Coronavirus) Non Linear Modelling IRAN GERMANY TURKEY 2021 2 01 127 129 http://joc.kntu.ac.ir/article-1-828-en.pdf 10.52547/joc.14.5.127
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Rapid COVID-19 Screening Based on the Blood Test using Artificial Intelligence Methods Soheil Mehralian mehralian@ee.kntu.ac.ir Effat Jalaeian Zaferani jalaeian@ee.kntu.ac.ir Shahrzad Shashaani Shahrzad.sh7798@gmail.com Farnaz Kashefinishabouri Farnaz.kashefi.n@gmail.com Mohammad Teshnehlab teshnehlab@eetd.kntu.ac.ir Hosein Ali Sokhandan personal023@bmi.ir Zahra Sadat Dibaji Forooshani atousadiba@yahoo.com Bina Montazer Bina.montazer@gmail.com Zeinab Joneidi zeinabdjoneidi@zumc.ac.ir Maryam Vafapeyvand m.vafapeivand@gmail.com Coronavirus Disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is spreading rapidly worldwide and has led to widespread deaths globally. As a result, the early diagnosis of patients with COVID-19 is vital to control this dangerous virus's release. There are two common diagnosing methods, chest computed tomography scan (CT-scan) and Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. The most significant disadvantages of RT-PCR molecular tests are the high cost and the long waiting time for test results. The common weaknesses of chest CT-scan are the need for a radiologist to analyze, a misdiagnosis of flu disease due to its similarity, and risky for pregnancy and infants. This article presents a low-cost, highly available method for early detection of COVID-19 based on Artificial Intelligence (AI) systems and blood tests. In this study, 6635 patient's blood tests are used. Experiments conducted using three machine learning algorithms. The results show that the proposed method can detect COVID-19 with an accuracy of %84 and an F1-score of %83. The trained model is being used in a real-world product through an online website called CODAS. Artificial intelligence Blood test Fuzzy system Neural network Support vector machine COVID-19 Screen 2021 2 01 131 140 http://joc.kntu.ac.ir/article-1-845-en.pdf 10.52547/joc.14.5.131
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Journal of Control JoC 2008-8345 2538-3752 10.52547/joc 2021 14 5 Optimal Robust LPV Control Design for Novel Covid-19 Disease reza Najarzadeh Rezanajarzadeh97@gmail.com maryam dehghani mdehghani@shirazu.ac.ir mohammad hassan asemani asemani@shirazu.ac.ir roozbeh abolpour r.abolpour@shirazu.ac.ir These days almost all countries around the world are struggling with coronavirus outbreak. If the governments and public health care systems don't take any action against this outbreak, it would have severe effects on human life, now and in the future. By doing so, there are several intervention strategies that could be implemented and as the result, the societies become more secure from the casualties of this virus. In this paper, we used a mathematical model of coronavirus epidemic transmission and by use of some LMIs, a robust LPV controller is designed which helps us to choose and use the intervention methods, effectively. By use of the proposed robust controller, the robustness and stability of the model against a wide range of uncertainties are approved. The final objective of this control design is to minimize the number of exposed and infected individuals in the compartmental model. In the end, it can be seen that the control strategies which are preventive action, good medical care, and sterilization of the environment, can highly reduce the negative effects of the coronavirus. Covid-19 mathematical model robust controller intervention strategies LMI uncertainties 2021 2 01 141 153 http://joc.kntu.ac.ir/article-1-834-en.pdf 10.52547/joc.14.5.141