@article {36788, title = {Observer-Based Adaptive Robust Control of Dual-Layer Multiagent Epidemic Model: Physical and Information Layers}, journal = {IET Control Theory \& Applications}, year = {2025}, abstract = {This paper proposes an innovative dual-layer multi-agent-based SIS epidemic model, incorporating a physical contact layer to model disease spread through travel or migration between cities, and an information layer to enable the sharing of infection data among healthcare providers across cities even without direct physical connections. An observer is designed to estimate the infected fraction in each city, utilising estimates from neighbouring cities connected in the physical layer in a distributed manner; these estimates are then leveraged in the information layer to synchronise each city{\textquoteright}s infection trajectory with a virtual leader. Additionally, the control input, typically formulated in multi-agent systems (MAS), is adopted as the sliding surface, with its stability demonstrated via Lyapunov analysis within the dual-layer SIS framework. An adaptive sliding mode control (ASMC) strategy is developed to address parameter uncertainties to reach this sliding surface, effectively integrating the physical and information layers{\textquoteright} dynamics to drive cities toward disease eradication. Finally, a numerical example is provided to validate the accuracy of the theoretical results.}, url = {https://doi.org/10.1049/cth2.70052} } @conference {36789, title = {Impact of the Effect Term on Convergence Speed in Multi-Agent Systems}, booktitle = {2024 10th International Conference on Control, Instrumentation and Automation (ICCIA)}, year = {2024}, publisher = {IEEE}, organization = {IEEE}, abstract = {The primary objective of this study is to analyze the speed at which the system reaches consensus in multi-agent systems (MASs) when the effect term (ET) is either present or absent. By examining this, the research seeks to understand how the ET impacts the overall effectiveness and efficiency of the system in achieving a unified agreement or goal among the agents. This involves evaluating whether the ET accelerates or decelerates the consensus process and determining its role in the performance dynamics of the MAS. The insights gained from this analysis could provide valuable information on optimizing MAS configurations for better coordination and control in various applications.}, url = {https://doi.org/10.1109/ICCIA65044.2024.10768135} } @conference {36790, title = {Multi-Agent Consensus Algorithms for a Dual-Layer Epidemic Model}, booktitle = {2024 10th International Conference on Control, Instrumentation and Automation (ICCIA)}, year = {2024}, publisher = {IEEE}, organization = {IEEE}, abstract = {This paper introduces a dual-layer approach for a multi-agent-based SIS model, comprising two distinct layers: the person-to-person contact layer and the information layer. The person-to-person contact layer represents interpersonal interactions within cities, while the information layer captures the exchange of data, such as the number of confirmed cases, among healthcare officials in each city. Furthermore, a state-observer-based consensus mechanism is employed to estimate the unknown states{\textemdash}specifically, the number of infected individuals{\textemdash}within the person-to-person contact layer, which is then utilized in the information layer. A numerical example is provided to validate the theoretical findings.}, url = {https://doi.org/10.1109/ICCIA65044.2024.10768141} } @article {34478, title = {Switched Epidemic Models: A Contact Rate Dependent Analysis}, journal = {Applied Mathematical Modelling}, year = {2024}, abstract = {This paper introduces a switched SQWVEAIR (Susceptible, Quarantined, Weak, Vaccinated Exposed, Asymptomatic, Infected, and Recovered) epidemic model considering changing contact rates in an infected society. It also takes into account the presence of vulnerable individuals as frontiers in vaccination, recognizing their societal importance. The qualitative analysis of the model involves two theorems on the positive invariance set and the positivity of the solutions. Additionally, it calculates the equilibria of the proposed model and analyzes their global stabilities using the Lyapunov functional technique, focusing on the basic reproduction number (R0) as a bifurcation value. To achieve globally uniformly exponential stability, it calculates the contact-rate-dependent average dwell time (CRDADT) for each stable and unstable subsystem, developing a Lyapunov function. It also derives sufficient conditions, expressed as linear matrix inequalities (LMIs), to ensure stability. A numerical example is provided to demonstrate the effectiveness of the theoretical analysis and validate our research findings.}, url = {https://doi.org/10.1016/j.apm.2024.01.016} } @article {32856, title = {Laminated optimization of non-uniform I-shaped beams under transversely loading with clamped-free boundary conditions}, journal = {Structures}, year = {2023}, abstract = {This paper intends to predict the best lamination stacking sequences for the web and both flanges of cantilever double-tapered beam exposed to an externally uniformly distributed force to achieve the maximum lateral buckling capacity with optimized mass and material cost. Vlasov{\textquoteright}s model along with the classical laminated plate theory is utilized for extracting the variational formulation in terms of\ lateral displacement\ and\ angle of rotation\ due to torsion. Considering a specific member, the Ritz method is employed to derive an analytical expression for the transverse buckling load as an explicit function of stiffness components. Through the technique of\ genetic algorithm, the optimum design of a lightweight multi-layer fibrous composite I-shaped beam with varying cross-sections that can sustain the maximum lateral buckling load is finally attained. The numerical results reveal that the endurable lateral buckling load of a selected model increases by about 56\% via the proposed optimization process.}, url = {https://www.sciencedirect.com/science/article/pii/S2352012422011778} } @article {32857, title = {Vaccination and isolation based control design of the COVID-19 pandemic based on adaptive neuro fuzzy inference system optimized with the genetic algorithm}, journal = {Evolving Systems}, year = {2023}, abstract = {The study of the COVID-19 pandemic is of pivotal importance due to its tremendous global impacts. This paper aims to control this disease using an optimal strategy comprising two methods: isolation and vaccination. In this regard, an optimized Adaptive Neuro-Fuzzy Inference System (ANFIS) is developed using the Genetic Algorithm (GA) to control the dynamic model of the COVID-19 termed SIDARTHE (Susceptible, Infected, Diagnosed, Ailing, Recognized, Threatened, Healed, and Extinct). The number of diagnosed and recognized people is reduced by isolation, and the number of susceptible people is reduced by vaccination. The GA generates optimal control efforts related to the random initial number of each chosen group as the input data for ANFIS to train Takagi{\textendash}Sugeno (T{\textendash}S) fuzzy structure coefficients. Also, three theorems are presented to indicate the positivity, boundedness, and existence of the solutions in the presence of the controller. The performance of the proposed system is evaluated through the mean squared error (MSE) and the root-mean-square error (RMSE). The simulation results show a significant decrease in the number of diagnosed, recognized, and susceptible individuals by employing the proposed controller, even with a 70\% increase in transmissibility caused by various variants.}, url = {https://link.springer.com/article/10.1007/s12530-022-09459-9} } @article {32854, title = {Multi-objective optimization of lateral stability strength of transversely loaded laminated composite beams with varying I-section}, journal = {Journal of Composite Materials}, year = {2022}, abstract = {In this research, the lateral buckling analysis and layup optimization of the laminated composite of web and flanges tapered thin-walled I-beams based on maximizing lateral-torsional stability strength and minimizing mass/cost of the structure are investigated. The classical lamination theory and Vlasov{\textquoteright}s model for thin-walled cross-section are adopted to establish the total potential energy for thin-walled symmetric balanced laminated beams with varying I-section. By implementing the Ritz method, an explicit formulation for the lateral-torsional buckling load of a double-tapered beam subjected to transverse loading is then derived in terms of the load height parameter and stiffness quantities. Subsequently, the optimal arrangements of layer sequences are obtained using the non-dominated sorting genetic algorithm (NSGA-II) and properly defined objective function. The critical factors of fitness function as lateral buckling strength and the mass of the structure with critical limitations as ply angle, number of layers for the web and flanges, and the thickness of all section walls are considered in this study. Finally, the optimal layer arrangement for the web and flanges are separately determined and discussed. The results show that the presented optimization procedure and layups patterns lead to increasing the lateral-torsional buckling capacity about 52\% compared to the conventional angle-ply and unidirectional layups for the web and flanges, respectively.}, url = {https://journals.sagepub.com/doi/abs/10.1177/00219983221088943} } @article {32855, title = {Nonlinear robust adaptive sliding mode control strategy for innate immune response to influenza virus}, journal = {IETE Journal of Research}, year = {2022}, abstract = {This paper aims to design a nonlinear robust adaptive sliding mode control strategy for a mathematical model describing the innate immune response to influenza virus infection. This model possesses seven state variables (respiratory tract epithelial cells in four possible states, namely: healthy, partially infected, infected, and resistant-to-infection, and interferon (IFN) molecules, natural killers, and viruses). This model is based on resistance-to-infection derived from IFN molecules and the removal of infected cells by natural killers. Two control strategies (vaccination and antiviral treatment) are introduced to eradicate the infection. First, a vaccination strategy is applied to convert healthy cells into resistant-to-infection ones inside the body of the susceptible individual. Second, the infected individual undergoes an antiviral treatment strategy that fights against the spread of the concentration of viruses and converts the healthy cells into resistant-to-infection ones simultaneously. The Lyapunov stability theorem is employed to analyse the stability of the desired strategies. Finally, the simulation results show that the goal is fulfilled satisfactorily.}, url = {https://www.tandfonline.com/doi/abs/10.1080/03772063.2022.2154282} } @inbook {32853, title = {Optimal control design of impulsive SQEIAR epidemic models with application to COVID-19}, booktitle = {Modeling, Control and Drug Development for COVID-19 Outbreak Prevention}, year = {2022}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, abstract = {According to the great importance and effectiveness of quarantine in the COVID-19 epidemic, this chapter presents a SEIAR-type model considering quarantined individuals (Q), called SQEIAR model. The main factor that has played a major role in the outbreak of COVID-19 around the world is traveling and immigration of people, which add to the population size impulsively. Therefore, an impulsive epidemic model of SQEIAR is considered to deal with the potential sudden increase in population caused by immigration or travel. Optimal control theory is presented to control and reduce the rate of disease spread in society within an optimal time. Optimal control is used to minimize an objective (cost) function over a free terminal time. Also, quarantine and antiviral treatment are used as control inputs. In the following, numerical simulations are given to prove the accuracy of the theoretical claims and applied to this infection{\textquoteright}s particular data. Moreover, numerical computations of the COVID-19 are compared with diseases like Ebola and Influenza. In addition, the controller is evaluated with system parameters identified by using actual data of China. Finally, the controller tuned with the estimated parameters of the Chinese data is applied to Spain{\textquoteright}s actual data to compare the quarantine and treatment policies in both countries.}, url = {https://link.springer.com/chapter/10.1007/978-3-030-72834-2_14} } @article {32845, title = {Fuzzy Sliding Mode Controller Design and Analysis of an SQEIAR Epidemic Model for COVID-19 to Determine the Quarantine Rate}, journal = {Journal of Control}, year = {2021}, abstract = {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 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.}, url = {https://joc.kntu.ac.ir/browse.php?a_id=820\&sid=1\&slc_lang=en} } @article {32850, title = {Linear Modeling of the Impact of Pests and Diseases on the Growth Process of Strawberry Plants in the State Space}, journal = {Journal of Horticultural Science}, year = {2021}, abstract = {Introduction\ Strawberry is a significant fruit due to its rich sources of vitamins and plenty of antioxidants and grows worldwide. Thus, studies that provide information on topics in strawberry growth are momentous. Strawberry production is often threatened by various pests. Therefore, pest management is one of the most critical points in strawberry cultivation and production that have to be considered. There are several pests that can have detrimental effects on strawberry production. For example, thrips is an important pest for strawberry in a greenhouse condition. There are many ways to deal with greenhouse pests; one of the best ways is to observe greenhouse hygiene and sanitation and use the proper chemical pesticides. Yet, it is impossible to predict the plant{\textquoteright}s growth stages in the usual ways to predict the time of using chemical pesticides. The time of each growth stage{\textquoteright}s occurrence can be predicted only by using simulation models and considering the factors affecting plant growth, such as environmental factors, pests, disease, and nutrition. To this end, this study aims to model the growth process of strawberry plants by considering pests and diseases{\textquoteright} impact.Materials and Methods\ Monitoring the growth stages is a critical component of a successful strawberry growth program. To harvest more, it is vital to develop effective predicting tools. There are several approaches to investigate the change in the size and form of planets based on some growth conditions over time. The best-known mechanism of analyzing the growth process mathematically is simulation modeling. Models can be used as an alternative for statistical analysis of harvest of\ {\textellipsis}}, url = {https://jhs.um.ac.ir/article_40473_en.html} } @article {32852, title = {Optimal Allocation of Vaccine and Antiviral Drugs for Influenza Containment over Delayed Multiscale Epidemic Model considering Time-Dependent Transmission Rate}, journal = {Computational and Mathematical Methods in Medicine}, year = {2021}, abstract = {In this study, two types of epidemiological models called {\textquotedblleft}within host{\textquotedblright} and {\textquotedblleft}between hosts{\textquotedblright} have been studied. The within-host model represents the innate immune response, and the between-hosts model signifies the SEIR (susceptible, exposed, infected, and recovered) epidemic model. The major contribution of this paper is to break the chain of infectious disease transmission by reducing the number of susceptible and infected people via transferring them to the recovered people group with vaccination and antiviral treatment, respectively. Both transfers are considered with time delay. In the first step, optimal control theory is applied to calculate the optimal final time to control the disease within a host{\textquoteright}s body with a cost function. To this end, the vaccination that represents the effort that converts healthy cells into resistant-to-infection cells in the susceptible individual{\textquoteright}s body is used as the first control input to vaccinate the susceptible individual against the disease. Moreover, the next control input (antiviral treatment) is applied to eradicate the concentrations of the virus and convert healthy cells into resistant-to-infection cells simultaneously in the infected person{\textquoteright}s body to treat the infected individual. The calculated optimal time in the first step is considered as the delay of vaccination and antiviral treatment in the SEIR dynamic model. Using Pontryagin{\textquoteright}s maximum principle in the second step, an optimal control strategy is also applied to an SEIR mathematical model with a nonlinear transmission rate and time delay, which is computed as optimal time in the first step. Numerical results are consistent with the analytical ones and corroborate our theoretical results.}, url = {https://www.hindawi.com/journals/cmmm/2021/4348910/} } @conference {32846, title = {Optimal Control of SEIR Epidemic Model Considering Nonlinear Transmission Rate and Time Delay}, booktitle = {2021 7th International Conference on Control, Instrumentation and Automation (ICCIA)}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, abstract = {In this study, an optimal control strategy is applied to the SEIR (Susceptible-Exposed-Infected-Recovered) epidemic model with nonlinear transmission rate and time-delay caused by vaccination and antiviral treatment. This paper aims to recover the susceptible people by vaccination and treat the infected people by antiviral treatment. The susceptible and infected people are moved to the recovered group with a time delay. Pontryagin{\textquoteright}s maximum principle is used to obtain the optimal control inputs and the optimal time. Numerical results are consistent with the analytical ones and corroborate our theoretical results.}, url = {https://ieeexplore.ieee.org/abstract/document/9403558} } @conference {32847, title = {Optimized ANFIS-based Control Design Using Genetic Algorithm to Obtain the Vaccination and Isolation Rates for the COVID-19}, booktitle = {2021 29th Iranian Conference on Electrical Engineering (ICEE)}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, abstract = {In this work, an Adaptive-Network-based Fuzzy Inference System (ANFIS) control is designed and optimized with the Genetic Algorithm (GA) to control the COVID-19 described by the SEIAR (Susceptible - Exposed - Infected - Asymptomatic - Recovered) epidemic model. This work aims to reduce the number of infected and susceptible people by isolation and vaccination, respectively. In this regard, the ANFIS-based controller is designed. The GA is employed to generate an optimal data set by minimizing the appropriate objective function to train the ANFIS algorithm. The obtained results are evaluated via simulation in MATLAB software to show the capability of the controller in overcoming the outbreak.}, url = {https://ieeexplore.ieee.org/abstract/document/9544298} } @article {32849, title = {Parameter estimation of MIMO two-dimensional ARMAX model based on IGLS method}, journal = {Control \& Cybernetics}, year = {2021}, abstract = {This paper presents an iterative method for the unbiased identification of linear Multiple-Input Multiple-Output (MIMO) discrete two-dimensional (2D) systems. The system discussed here has Auto-Regressive Moving-Average model with exogenous inputs (ARMAX model). The proposed algorithm functions on the basis of the traditional Iterative Generalized Least Squares (IGLS) method. In summary, this paper proposes a two-dimensional Multiple-Input Multiple-Output Iterative Generalized Least Squares (2DMIGLS) algorithm to estimate the unknown parameters of the ARMAX model. Finally, simulation results show the efficiency and accuracy of the presented algorithm in estimating the unknown parameters of the model in the presence of colored noise.}, url = {https://yadda.icm.edu.pl/baztech/element/bwmeta1.element.baztech-8cbcffbe-2e29-4019-9028-7894287a2556} } @conference {32848, title = {Stability Analysis of a New Switched SEIAR-Vac-Iso Epidemic Model for the COVID-19}, booktitle = {2021 29th Iranian Conference on Electrical Engineering (ICEE)}, year = {2021}, publisher = {IEEE}, organization = {IEEE}, abstract = {In this paper, a new switched SEIAR-Vac-Iso (Susceptible, Exposed, Infected, Asymptomatic, Recovered, Vaccinated, Isolated) epidemic model is introduced and investigated with application to COVID-19 for the first time. Two theorems concerning the positivity and boundedness of the solutions are proved. Then, the basic reproduction number and the equilibrium points of the new model are calculated. The stability of the switched system is also investigated by developing a Lyapunov function and using the switching invariance principle, then the stability conditions of the systems are obtained. Numerical simulations are presented to verify the accuracy of theoretical results.}, url = {https://ieeexplore.ieee.org/abstract/document/9544173} } @article {32843, title = {Optimal control design of impulsive SQEIAR epidemic models with application to COVID-19}, journal = {Chaos, Solitons \& Fractals}, year = {2020}, abstract = {This paper presents a SEIAR-type model considering quarantined individuals (Q), called SQEIAR model. The dynamic of SQEIAR model is defined by six ordinary\ differential equations\ that describe the numbers of Susceptible, Quarantined, Exposed, Infected, Asymptomatic, and Recovered individuals. The goal of this paper is to reduce the size of susceptible, infected, exposed and asymptomatic groups to consequently eradicate the infection by using two actions: the quarantine and the treatment of infected people. To reach this purpose, optimal control theory is presented to control the epidemic model over free terminal optimal time control with an optimal cost. Pontryagin{\textquoteright}s maximum principle is used to characterize the optimal controls and the optimal final time. Also, an impulsive epidemic model of SQEIAR is considered to deal with the potential suddenly increased in population caused by immigration or travel. Since this model is suitable to describe the COVID-19 pandemic, especial attention is devoted to this case. Thus, numerical simulations are given to prove the accuracy of the theoretical claims and applied to the particular data of this infection. Moreover, numerical computations of the COVID-19 are compared with diseases like Ebola and Influenza. In addition, the controller is evaluated with system parameters identified by using actual data of China. Finally, the controller tuned with the estimated parameters of the Chinese data is applied to the actual data of Spain to compare the quarantine and treatment policies in both countries.}, url = {https://www.sciencedirect.com/science/article/pii/S0960077920304513} } @article {32844, title = {Parameter Estimation and Prediction of COVID-19 Epidemic Turning Point and Ending Time of a Case Study on SIR/SQAIR Epidemic Models}, journal = {Computational and Mathematical Methods in Medicine}, year = {2020}, abstract = {In this paper, the SIR epidemiological model for the COVID-19 with unknown parameters is considered in the first strategy. Three curves (,\ ,\ and\ )\ are fitted to the real data of South Korea, based on a detailed analysis of the actual data of South Korea, taken from the Korea Disease Control and Prevention Agency (KDCA). Using the least square method and minimizing the error between the fitted curve and the actual data, unknown parameters, like the transmission rate, recovery rate, and mortality rate, are estimated. The goodness of fit model is investigated with two criteria (SSE and RMSE), and the uncertainty range of the estimated parameters is also presented. Also, using the obtained determined model, the possible ending time and the turning point of the COVID-19 outbreak in the United States are predicted. Due to the lack of treatment and vaccine, in the next strategy, a new group called quarantined people is added to the proposed model. Also, a hidden state, including asymptomatic individuals, which is very common in COVID-19, is considered to make the model more realistic and closer to the real world. Then, the SIR model is developed into the SQAIR model. The delay in the recovery of the infected person is also considered as an unknown parameter. Like the previous steps, the possible ending time and the turning point in the United States are predicted. The model obtained in each strategy for South Korea is compared with the actual data from KDCA to prove the accuracy of the estimation of the parameters.}, url = {https://www.hindawi.com/journals/cmmm/2020/1465923/} } @article {32842, title = {Observer-based adaptive PI sliding mode control of developed uncertain SEIAR influenza epidemic model considering dynamic population}, journal = {Journal of theoretical biology}, year = {2019}, abstract = {This paper presents a new Susceptible, Exposed, Infected, Asymptomatic, and Recovered individuals (SEIAR) model for influenza considering a dynamic population. In the given model, the possibility of transmission of asymptomatic individuals (infectious with no visible symptoms) to infected individuals (infectious exhibiting symptoms) is considered. The basic reproduction number and the equilibrium points of the new model are given while the stability of the equilibrium points is analyzed by using the Jacobian matrix. Then a multi-controller scheme consisting of a parallel controller defined by two control inputs (vaccination and antiviral treatment) is given where both of them are based on Proportional-Integral (PI) and sliding mode controllers, which are parameterized adaptively to guarantee the convergence of trajectories to the sliding surface with minimum amount of chattering. The proposed control scheme is able to asymptotically stabilize the SEIAR model in the sense of eradication of the infected and susceptible individuals. Moreover, a (reduced-order) observer is designed to estimate the actual state variables that are used in the implementation of the control signals. By using MATLAB{\textregistered} software, a comprehensive simulation and evaluation of treatment and performance are carried out to support the presented theoretical results.}, url = {https://www.sciencedirect.com/science/article/pii/S0022519319303273} } @conference {32841, title = {Robust stability for affine TS fuzzy impulsive control systems subject to parametric uncertainties}, booktitle = {2019 27th Iranian Conference on Electrical Engineering (ICEE)}, year = {2019}, publisher = {IEEE}, organization = {IEEE}, abstract = {The main objective of this paper is to investigate the robust stability problem of affine fuzzy impulsive control systems in which the system is presented by affine Takagi-Sugeno fuzzy model. By using extended Lyapunov stability theory, some matrix inequalities conditions are derived to guarantee the stability of affine Takagi-Sugeno fuzzy impulsive control systems subject to parametric uncertainties. A numerical example is given to confirm the analytical results and illustrate the effectiveness of the proposed strategy.}, url = {https://ieeexplore.ieee.org/abstract/document/8786425} }