Arithmetic optimization algorithm based PID control for reduced order motorized wheelchairs with real time MIL SIL PIL validation

Effective control of motorized wheelchairs needs methods with capabilities for stability, rapid response, accuracy, and robustness against nonlinearities and disturbances common in electromechanical systems. In this article, an optimized PID controller based on an Arithmetic Optimization Algorithm (AOA), known as AOA-PID, strategy is introduced. A full wheelchair model and an optimization model are used, offering a chance for a reduction in computation cost with retention of basic system dynamics. Experimental research on the role of PID factors will be conducted, followed by performance analysis on two axes: firstly, comparative research with multiple references on PID optimization methods, including Sine Cosine Algorithms (SCA), Kepler Optimization Algorithms (KOA), Salp Swarm Algorithms (SSA), Puma Optimizer Algorithms (POA), and Particle Swarm Optimization Algorithms (PSO); and secondly, comparative research on traditional and modern methods. The research result illustrates that AOA-PID exhibits quicker response and controlled overshoots with zero error and an extremely low IAE value, indicating simultaneous enhancement on stability, accuracy, and robustness. Additionally, Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), and Processor-in-the-Loop (PIL) testing confirms the controller's capability to maintain high performance within an embedded system with low CPU consumption that meets real-time processing. As a result, AOA-PID strategy proves an efficient and highly capable strategy on assistive mobility control with significant improvements on safety, stability, and accuracy.

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Publication Details

Journal
Scientific Reports
Published
2026-04-13
DOI
https://doi.org/10.1038/s41598-026-47689-y
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
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article

Arithmetic optimization algorithm based PID control for reduced order motorized wheelchairs with real time MIL SIL PIL validation

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Scientific Reports
Gaze Tracking and Assistive Technology
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Arithmetic optimization algorithm based PID control for reduced order motorized wheelchairs with real time MIL SIL PIL validation

Mohamed Kmich, Mhamed Sayyouri, Zakaria Chalh, Hicham Karmouni, Hassan M. Hussein Farh, Inssaf Harrade, Abdullrahman A. Al-Shamma’a
article en

Abstract

Effective control of motorized wheelchairs needs methods with capabilities for stability, rapid response, accuracy, and robustness against nonlinearities and disturbances common in electromechanical systems. In this article, an optimized PID controller based on an Arithmetic Optimization Algorithm (AOA), known as AOA-PID, strategy is introduced. A full wheelchair model and an optimization model are used, offering a chance for a reduction in computation cost with retention of basic system dynamics. Experimental research on the role of PID factors will be conducted, followed by performance analysis on two axes: firstly, comparative research with multiple references on PID optimization methods, including Sine Cosine Algorithms (SCA), Kepler Optimization Algorithms (KOA), Salp Swarm Algorithms (SSA), Puma Optimizer Algorithms (POA), and Particle Swarm Optimization Algorithms (PSO); and secondly, comparative research on traditional and modern methods. The research result illustrates that AOA-PID exhibits quicker response and controlled overshoots with zero error and an extremely low IAE value, indicating simultaneous enhancement on stability, accuracy, and robustness. Additionally, Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), and Processor-in-the-Loop (PIL) testing confirms the controller's capability to maintain high performance within an embedded system with low CPU consumption that meets real-time processing. As a result, AOA-PID strategy proves an efficient and highly capable strategy on assistive mobility control with significant improvements on safety, stability, and accuracy.

Scientific Reports
Imam Mohammad ibn Saud Islamic University (SA), Sidi Mohamed Ben Abdellah University (MA), University of Hassan II Casablanca (MA)
Affordable and clean energy
Openalex Percentile: Top 23%
Gaze Tracking and Assistive Technology
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