Design and Analysis of a Novel Generalized Continuous Tracking Differentiator

Abdul-Adheem, Wameedh Riyadh; Ibraheem, Ibraheem Kasim; Humaidi, Amjad J.; Alkhayyat, Ahmed; Maher, Rami A.; Abdulkareem, Ahmed Ibraheem; Azar, Ahmad Taher

doi:10.1016/j.asej.2021.101656

Cited by 9 publications

(7 citation statements)

References 26 publications

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“…MSE measures the error quantity and is used for minimization as well. MSE is also often used as a performance metric in regression problems [25,26]. Table 2 displays the mathematical formulas of the objective functions.…”

Section: öZen Et Al (2021) Use Machine Learning Methods To Make Predi...mentioning

confidence: 99%

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COVID-19 Diagnosis from Blood Gas Using Multivariate Linear Regression

Ayata,

Seyyarer

2024

Hittite Journal of Science and Engineering

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With the impact of the COVID-19 outbreak, almost all scientists and nations began to show great interest in the subject for a long time. Studies in the field of outbreak, diagnosis and prevention are still ongoing. Issues such as methods developed to understand the spread mechanisms of the disease, prevention measures, vaccine and drug research are among the top priorities of the world agenda. The accuracy of the tests applied in the outbreak management has become extremely critical. In this study, it is aimed to obtain a function that finds the positive or negative COVID-19 test from the blood gas values of individuals by using Machine Learning methods to contribute to the outbreak management. Using the Multivariate Linear Regression (MLR) model, a linear function is obtained to represent the COVID-19 dataset taken from the Van province of Turkey. The data set obtained from Van Yüzüncü Yıl University Dursun Odabaş Medical Center consists of blood gas analysis samples (109 positive, 1146 negative) taken from individuals. It is thought that the linear function to be obtained by using these data will be an important method in determining the test results of individuals. Gradient Descent optimization methods are used to find the optimum values of the coefficients in the function to be obtained. In the study, the RMSProp optimization algorithm has a success rate of 58-91.23% in all measurement methods, and it is seen that it is much more successful than other optimization algorithms.

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Section: öZen Et Al (2021) Use Machine Learning Methods To Make Predi...mentioning

confidence: 99%

“…Objective Functions [25,26]. FE is applied to data sets such as images and audio, while FS is applied to more sensitive data.…”

Section: Tablementioning

confidence: 99%

COVID-19 Diagnosis from Blood Gas Using Multivariate Linear Regression

Ayata,

Seyyarer

2024

Hittite Journal of Science and Engineering

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“…Note: V 1 (100), V 2 (110), V 3 (010), V 4 (011), V 5 (001), V 6 (101) Ajel et al, 2021;Al-Qassar et al, 2021a,b;Bansal et al, 2021;Azar et al, ,b,c,d,e,f,g,h,i,j, 2020aNajm et al, 2022Najm et al, , 2021aNajm et al, ,b 2020Elkholy et al, 2020a,b;Mohamed et al, 2020;Ibrahim et al, 2020;Sayed et al, 2023Sayed et al, , 2020Samanta et al, 2018 ;Mukherjee et al, 2014;Fekik et al, 2022Fekik et al, . 2021aFekik et al, ,b,c, 2020aFekik et al, , 2019Fekik et al, , 2018aDaraz et al, 2022Daraz et al, , 2021Pilla et al, 2021aPilla et al, ,b, 2020Pilla et al, , 2019Abdul-Adheem et al, 2022Liu et al, 2020;Bouchemha et al, 2021;Gorripotu et al, 2021Gorripotu et al, , 2019Drhorhi et al, 2021 ;Kumar et al, 2018Kumar et al, , 2021Acharyulu et al, 2021;Hamiche et al, 2021;Mittal et al, 2021;Pham et al, 2021Pham et al, , 2018Pham et al, , 2017aSambas et al, 2021a,b;Khan et al, 2020a,b;Khennaoui et al, 2020a,b;Kammogne et al, 2020;Alain et al, 2020…”

Section: Proposed Controllermentioning

confidence: 99%

A Design and Implementation of a New Control Based on Petri Nets for Three Phase PWM-Rectifier

Fekik

Hamida

Kais

et al. 2023

International Journal of Service Science, Management, Engineering, and Technology

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This article introduces a novel and effective diagram based on direct instantaneous power control (DPC) of a PWM-controlled rectifier connected to the grid without a switching table. An optimum control vector of the PWM rectifier's input voltage, which depends on the switching states determined by a Petri nets controller, is adopted. This approach limits the instantaneous detection errors of reactive and active powers, maintains the DC bus voltage at a reference level, and ensures current close to a sinusoidal wave, guaranteeing operation at a unit power factor. The instantaneous tracking errors of active and reactive powers and the angular position of the voltage are used as input variables for the proposed controller, which then selects the best control vector for the converter based on the transition of a Petri net. The significant advantages of DPC based on Petri nets compared to traditional switching tables are that hysteresis comparators are not required, and the classical regulation of active and reactive powers is achieved in all sectors. Simulation and testing findings demonstrated excellent performance, supporting the viability of the suggested control approach using Petri nets.

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“…As shown in equations ( 8 ) and ( 9 ), the error becomes the input to the tracking differentiator rather than the reference signal, and the result is a smooth original signal and its derivative that avoids chatter in the output signal. In the proposed TD, the sigmoid function ( 2 ) and Elliott squash function (equation ( 9 ) given in [ 26 ] are utilized instead of the sign function used in the conventional tracking differentiator proposed by [ 18 ], however.…”

Section: Active Disturbance Rejection Control Designmentioning

confidence: 99%

“…To avoid the problem of chatter, a conventional super twisting controller (CST-SMC) is utilized. This offers a second-order sliding mode in the nonlinear version of the PI controller, which is designed for a system with a relative degree of one [ 19 , 26 ]. The STC-SM guarantees that trajectories can reach the sliding surface and converge in a finite amount of time because the trajectories twist around the origin of the sliding surface; the STC-SM thus guarantees this continuity and convergence in finite time by replacing the term b ∫sign( σ ) with a continuous function, which has several advantages.…”

Section: Active Disturbance Rejection Control Designmentioning

confidence: 99%

Mathematical Modeling and Control of COVID-19 Using Super Twisting Sliding Mode and Nonlinear Techniques

Aljuboury

Abedi

Shukur

et al. 2022

Computational Intelligence and Neuroscience

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Since the outbreak of the COVID-19 epidemic, several control strategies have been proposed. The rapid spread of COVID-19 globally, allied with the fact that COVID-19 is a serious threat to people’s health and life, motivated many researchers around the world to investigate new methods and techniques to control its spread and offer treatment. Currently, the most effective approach to containing SARS-CoV-2 (COVID-19) and minimizing its impact on education and the economy remains a vaccination control strategy, however. In this paper, a modified version of the susceptible, exposed, infectious, and recovered (SEIR) model using vaccination control with a novel construct of active disturbance rejection control (ADRC) is thus used to generate a proper vaccination control scheme by rejecting those disturbances that might possibly affect the system. For the COVID-19 system, which has a unit relative degree, a new structure for the ADRC has been introduced by embedding the tracking differentiator (TD) in the control unit to obtain an error signal and its derivative. Two further novel nonlinear controllers, the nonlinear PID and a super twisting sliding mode (STC-SM) were also used with the TD to develop a new version of the nonlinear state error feedback (NLSEF), while a new nonlinear extended state observer (NLESO) was introduced to estimate the system state and total disturbance. The final simulation results show that the proposed methods achieve excellent performance compared to conventional active disturbance rejection controls.

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Design and Analysis of a Novel Generalized Continuous Tracking Differentiator

Cited by 9 publications

References 26 publications

COVID-19 Diagnosis from Blood Gas Using Multivariate Linear Regression

COVID-19 Diagnosis from Blood Gas Using Multivariate Linear Regression

A Design and Implementation of a New Control Based on Petri Nets for Three Phase PWM-Rectifier

Mathematical Modeling and Control of COVID-19 Using Super Twisting Sliding Mode and Nonlinear Techniques

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