Comparative Analysis of Airflow Regulation in Ventilator Systems Using Various Control Strategies

Shanan, Dhiyaa Sheltag; Kadhim, Saleem Khalefa

doi:10.18280/jesa.560512

Cited by 2 publications

(2 citation statements)

References 30 publications

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“…There are two phases that can be found in the SMC strategy: the reaching phase and the sliding phase. The perturbations will be compensated and rejected during the sliding phase [34][35][36]. However, during the reaching phase, disturbances and model uncertainties affect the system.…”

Section: Control Designmentioning

confidence: 99%

Design of a Robust Controller Based on Barrier Function for Vehicle Steer-by-Wire Systems

Husain,

Al-Dujaili,

Jaber

et al. 2024

WEVJ

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In this research paper, a recent robust control scheme was proposed and designed for a VSbW (vehicle steer-by-wire) system. Using an integral sliding mode control (ISMC) design based on barrier function (ISMCbf) could improve the robustness of ISMCs. This control scheme, due to the characteristics of the barrier function, can improve the robustness of the proposed controller better than that based on the conventional SMC or integral SMC (ISMC). The ISMCbf scheme exhibits all the benefits of the conventional ISMC with the addition of two main advantages: it does not require prior knowledge of perturbation bounds or their derivatives, and it can effectively eliminate the chattering phenomenon associated with the classical ISMC due to the smooth characteristics of the barrier function. On the other hand, in terms of the design implementation, the ISMCbf is simpler than the ISMC. In this study, the mathematical dynamical model of the VSbW plant was first presented. Then, the control design of the ISMCbf scheme was developed. The numerical results showed that the proposed scheme is superior to the conventional ISMC. The superiority of the proposed ISMCbf controller versus the classical ISM has been evaluated under three different uncertain conditions, and three scenarios can be deduced: a slalom path, quick steering, and shock disturbance rejection. Furthermore, a comparative analysis with other controllers from the literature has further been established to show the effectiveness of the proposed ISMCbf.

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Section: Control Designmentioning

confidence: 99%

Design of a Robust Controller Based on Barrier Function for Vehicle Steer-by-Wire Systems

Husain,

Al-Dujaili,

Jaber

et al. 2024

WEVJ

View full text Add to dashboard Cite

show abstract

“…The mechanical ventilation device, comprising an electrically powered blower unit, generates the requisite pressure for patient lung inflation (Po) via a hose medium. Mathematical models have been instrumental in resolving complex engineering challenges [11,12] and are similarly utilized to elucidate lung mechanics and enhance mechanical ventilation therapy [13]. A prevalent approach in existing literature involves the use of a single-compartment lung model, accounting for lung elastance (inverse of compliance) and airway resistance [14].…”

Section: Mathematical Modeling Of Ventilator Systemmentioning

confidence: 99%

Enhancing Artificial Ventilator Systems: A Comparative Analysis of Traditional and Nonlinear PID Controllers

Sheltag,

Kadhim

2024

MMEP

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In the context of critical medical equipment, particularly ventilators, the Corona Virus Disease 2019 (COVID-19) pandemic has heightened the importance of reliable respiratory support systems. Ventilators, designed to aid patient breathing, confront the challenge of delivering consistent air pressure and flow. This study explores the effectiveness of two control methods in ventilator systems: conventional Proportional-Integral-Derivative (PID) control and an advanced nonlinear PID control. The former employs a fixed formula for system regulation, while the latter adopts an adaptive mechanism, offering potential improvements in responsiveness to patient-specific needs. This investigation centers on the formulation and generalization of a robust, calculus-based controller for ventilators, with a particular focus on the nonlinear control method. The efficiency of these control methods in ventilator units was assessed, comparing traditional PID and nonlinear PID controllers. It was found that both methods exhibited an equivalent error percentage between reference and actual air pressures, quantified at approximately 0.94 mbar. This similarity highlights the effectiveness of the nonlinear PID controller, matching the precision of the traditional approach. Crucially, the nonlinear PID controller demonstrated a faster response time, indicating an enhanced capability for rapid adjustments in response to sudden patient demand changes. This feature is particularly significant in critical care environments, where swift adaptation of ventilator settings is essential for patient safety. The study emphasizes the control systems of ventilators, rather than their complete mechanical design, with the term 'error' specifically referring to the variance between desired and actual air pressures. The results of this research suggest that the nonlinear PID controller represents a significant advancement over existing methods. Its rapid response capabilities offer a promising avenue for improving patient safety and adaptability in challenging clinical scenarios. The investigation underscores the potential of nonlinear PID control in ventilator systems, positioning it as a superior alternative in specific medical contexts. This work contributes to the ongoing development of more responsive and patient-tailored approaches in mechanical ventilation, highlighting the convergence of advanced control theory and practical healthcare applications.

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Comparative Analysis of Airflow Regulation in Ventilator Systems Using Various Control Strategies

Cited by 2 publications

References 30 publications

Design of a Robust Controller Based on Barrier Function for Vehicle Steer-by-Wire Systems

Design of a Robust Controller Based on Barrier Function for Vehicle Steer-by-Wire Systems

Enhancing Artificial Ventilator Systems: A Comparative Analysis of Traditional and Nonlinear PID Controllers

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