{"id":11970,"date":"2026-09-06T09:58:00","date_gmt":"2026-09-06T06:58:00","guid":{"rendered":"https:\/\/en.coeng.uobaghdad.edu.iq\/?p=11970"},"modified":"2026-09-06T09:58:00","modified_gmt":"2026-09-06T06:58:00","slug":"phd-dissertation-defense-at-the-university-of-baghdad-on-developing-a-control-and-monitoring-system-for-a-medical-robot-via-iot-and-soft-computing","status":"publish","type":"post","link":"https:\/\/en.coeng.uobaghdad.edu.iq\/?p=11970","title":{"rendered":"PhD Dissertation Defense at the University of Baghdad on Developing a Control and Monitoring System for a Medical Robot via IoT and Soft Computing"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row][vc_column][vc_column_text css=&#8221;&#8221;]<\/p>\n<p>On Wednesday, September 2, 2026, at 9:00 AM, in the Smart Hall, the Department of Electrical Engineering at the College of Engineering, University of Baghdad, hosted the PhD thesis defense of student Noor Sabah Mohammed Ali, titled:<\/p>\n<p>&#8220;Development of Monitoring and Control Algorithms for a Medical Robot Using Internet of Things and Soft Computing Techniques&#8221;<\/p>\n<p>The thesis was supervised jointly by Assistant Professor Dr. Muna Hadi Saleh and Professor Dr. Nizar Hadi Abbas, as part of the requirements for obtaining a PhD degree in Electrical Engineering (Control and Computer Engineering).<\/p>\n<p>The research focused on the development and evaluation of monitoring and control algorithms for a lower-limb rehabilitation exoskeleton robot utilizing Internet of Things (IoT) and soft computing technologies. The proposed system was designed for a planar two-degree-of-freedom (2-DOF) robot representing the hip and knee joints. The dynamic model of the robot was derived using both Lagrange and Newton-Euler formulations for cross-verification and to ensure simulation accuracy.<\/p>\n<p>&nbsp;<\/p>\n<p>Key Scientific Contributions and Outcomes:<\/p>\n<p>&nbsp;<\/p>\n<ol>\n<li>Development of Advanced Smart Control Strategies:<\/li>\n<\/ol>\n<p>Designing and evaluating three intelligent control strategies based on hybrid systems and fractional-order calculus. The hybrid controller based on Computed Torque Control, Super-Twisting, and Fractional-Order Fuzzy PID (HCT-ST-FFOPID) demonstrated field superiority by achieving the highest stability, recording the lowest Integral Time Absolute Error (ITAE) values of 0.8479 for the first link and 0.6778 for the second link in non-linear tracking tests.<\/p>\n<ol start=\"2\">\n<li>Development of an Innovative Hybrid Optimization Algorithm:<\/li>\n<\/ol>\n<p>Achieving high-precision tuning of controller operational parameters using an innovative optimization algorithm named IElk-GM. This hybrid technique combines the optimization behaviors of Elk Herds, Grey Wolves, and Multi-Verse Optimizer, contributing to maximum response efficiency under external disturbances and parameter uncertainties.<\/p>\n<ol start=\"3\">\n<li>Construction of a Dual-Mode Control and Monitoring Framework (Online \/ Offline):<\/li>\n<\/ol>\n<p>-Online Cloud Mode: Enabling the medical therapist to perform real-time remote control and monitoring via a cloud dashboard hosted on an Amazon EC2 environment and integrated with AWS IoT Core, MQTT, Node-RED, and MATLAB\/Simulink. This allowed secure execution of start, stop, emergency, and reset commands, along with instant synchronization of patient and robot feedback data.<\/p>\n<p>-Offline Local Mode: Developing a local voice-control system based on a hybrid architecture combining MATLAB, Python, and the Vosk speech recognition engine enhanced with fuzzy logic techniques. The system achieved high response accuracy ranging between 80% and 95%, with ultra-fast real-time processing of voice commands.<\/p>\n<p>The practical results of the research demonstrated the feasibility of integrating intelligent control, algorithmic optimization, IoT-based cloud monitoring, and voice interaction into a unified framework that enhances the robustness and accuracy of medical rehabilitation robots.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_gallery interval=&#8221;3&#8243; images=&#8221;11973&#8243; img_size=&#8221;large&#8221; css=&#8221;&#8221;][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_column_text css=&#8221;&#8221;] On Wednesday, September 2, 2026, at 9:00 AM, in the Smart Hall, the Department of Electrical Engineering at &#8230; <a class=\"cz_readmore\" href=\"https:\/\/en.coeng.uobaghdad.edu.iq\/?p=11970\"><i class=\"fa fa-angle-left\" aria-hidden=\"true\"><\/i><span>\u0627\u0644\u0645\u0632\u064a\u062f<\/span><\/a><\/p>\n","protected":false},"author":165,"featured_media":11972,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[15,31],"tags":[],"class_list":["post-11970","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-electrical-engineering","category-thesis"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.7 - 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