Research Article Adaptive Fuzzy Sliding Mode Control of a Pressure-Controlled Artificial Ventilator Ibrahim M. Mehedi , 1,2 Heidir S. M. Shah, 1 Ubaid M. Al-Saggaf , 1,2 Rachid Mansouri , 3 and Maamar Bettayeb 4 1 Department of Electrical and Computer Engineering (ECE), King Abdulaziz University, Jeddah 21589, Saudi Arabia 2 Center of Excellence in Intelligent Engineering Systems (CEIES), King Abdulaziz University, Jeddah 21589, Saudi Arabia 3 Laboratoire de Conception et Conduite des Systemes de Production (L2CSP), Tizi-Ouzou 15000, Algeria 4 Electrical Engineering Department, University of Sharjah, Sharjah, UAE Correspondence should be addressed to Ibrahim M. Mehedi; imehedi@kau.edu.sa Received 31 May 2021; Revised 8 June 2021; Accepted 12 June 2021; Published 24 June 2021 Academic Editor: Dilbag Singh Copyright © 2021 Ibrahim M. Mehedi et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is paper presents the application of adaptive fuzzy sliding mode control (AFSMC) for the respiratory system to assist the patients facing difficulty in breathing. e ventilator system consists of a blower-hose-patient system and patient’s lung model with nonlinear lung compliance. e AFSMC is based on two components: singleton control action and a discontinuous term. e singleton control action is based on fuzzy logic with adjustable tuning parameters to approximate the perfect feedback line- arization control. e switching control law based on the sliding mode principle aims to minimize the estimation error between approximated single fuzzy control action and perfect feedback linearization control. e proposed control strategy manipulated the airway flow delivered by the ventilator such that the peak pressure will remain under critical values in presence of unknown patient-hose-leak parameters and patient breathing effort. e closed-loop stability of AFSMC will be proven in the sense of Lyapunov. For comparative analysis, classical PID and sliding mode controllers are also designed and implemented for me- chanical ventilation problems. For performance analysis, numerical simulations were performed on a mechanical ventilator simulator. Simulation results reveal that the proposed controller demonstrates better tracking of targeted airway pressure compared with its counterparts in terms of faster convergence, less overshoot, and small tracking error. Hence, the proposed controller provides useful insight for its application to real-world scenarios. 1. Introduction Several new viruses, epidemics, and even pandemics have emerged in the past 20 years. 774 people have been killed by the severe acute respiratory syndrome (SARS) that first emerged in mid-November 2002 in the Guangdong prov- ince, China [1]. In 2009, the World Health Organization (WHO) had declared a new global pandemic called H1N1 influenza. Although the confirmed number of deaths by WHO are 18,500, Dawood [2] in his studies estimates the actual number should be between 151,700 and 575,400. e most recent is the Middle East respiratory syndrome (MERS-CoV) in 2012 with 806 associated deaths reported in December 2018 mostly in Saudi Arabia [3]. Before the pandemic COVID-19 where to date, over 50 million people have been contacted with the disease with over 1 million deaths recorded since its discovery in the Wuhan province, China, in December 2019. e common cause of death for patients who contracted these diseases are acute respiratory distress syndrome (ARDS) where according to a study, 40 percent of critically ill COVID-19 patients developed this respiratory failure [4–7]. In most cases of ARDS, patients will have to be supported with mechanical ventilation to assist or replace their spontaneous breathing [8]. e earliest usage of mechanical ventilators as a device to provide ventilatory assistance can be traced back to the 18th Hindawi Journal of Healthcare Engineering Volume 2021, Article ID 1926711, 10 pages https://doi.org/10.1155/2021/1926711