Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems
Ayoub, Abdurahman Basil
Unknown Affiliation
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Nonlinear Model Predictive Control of a Magnetic Levitation System Using Artificial Protozoa Optimizer Noaman, Mohanad N.; Ayoub, Abdurahman Basil; Mahmood, Saif S.
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1668

Abstract

A magnetic levitation system (Maglev) is a sensitive, multi-parameter, nonlinear, and unstable system that is utilized to levitate a ferromagnetic object in free space. Due to its vast applications, various research studies in the field of control strategy have become extremely important and challenging. This work proposes the design of a nonlinear model predictive (NMPC) control scheme for the object position control against the nonlinearities and uncertainties of a Maglev system. A novel bio-inspired Artificial Protozoa Optimization (APO) algorithm is used to fine-tune the NMPC parameters, which include best weighting matrices ( ), shorter prediction horizons ( ), and shorter time steps ( ) to minimize the objective cost function. The effective performance of the NMPC is verified using simulation-based results in MATLAB. The CasADi toolbox is utilized to solve nonlinear optimization problems and handle the nonlinearity of the Maglev system model. Simulations are implemented for three trajectories tracking (step, sine, and square) with 20% and without Maglev parameters perturbations. To prove the superiority of the proposed controller, comparisons are made with the conventional Linear Quadratic Regulator (LQR) and proportional-integral-derivative (PID) controllers. Two performance indices are introduced, Integral of Squared Error (ISE) and Integral of Absolute Error (IAE), to examine the tracking performances of the NMPC, LQR, and PID controller.  The NMPC controller has shown more efficient performance and accurate results than other controllers. The contributions of this work include a new optimization technique of APO, a new engineering application of the APO integrated with NMPC to control a Maglev system, consideration of inherent nonlinearities and system constraints, and robustness improvement under perturbation.
NMPC Based-Trajectory Tracking and Obstacle Avoidance for Mobile Robots Qasim, Mohammed Salim; Ayoub, Abdurahman Basil; Abdulla, Abdulla Ibrahim
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1605

Abstract

This paper presents the design of a Nonlinear Model Predictive Controller (NMPC) for a wheeled Omnidirectional Mobile Robot (OMR) in order to track a desired trajectory in the presence of previously unknown static and dynamic obstacles in the environment around the robot. A laser rangefinder sensor is used to detect the obstacles where each obstacle occupies numerous points of every sensor reading. The points that belong to each obstacle are then clustered together using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. This research introduces a novel approach to represent obstacles as multiple rotated ellipses, enabling a more accurate representation of complex obstacle shapes without overestimating their boundaries, thereby allowing the robot to navigate through narrow passages. CoppeliaSim robotic simulator is utilized to create the virtual simulation environment as well as simulate the OMR dynamics. MATLAB with the help of the CasADi toolbox is used for the process of the laser rangefinder readings and the implementation of NMPC, respectively.  To validate the effectiveness and robustness of the proposed approach, three simulation scenarios are conducted, each involving distinct trajectories and varying densities of static and/or dynamic obstacles. The proposed control architecture exhibits remarkable performance, enabling the OMR to effectively navigate through narrow passages and avoid multiple static and dynamic obstacles while closely adhering to the desired trajectory.
Design of a Robust Component-wise Sliding Mode Controller for a Two-Link Manipulator Qasim, Mohammed; Abdulla, Abdulla Ibrahim; Ayoub, Abdurahman Basil
Journal of Robotics and Control (JRC) Vol. 6 No. 2 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i2.25632

Abstract

Compared to conventional Multiple-Input Multiple-Output (MIMO) Sliding Mode Control (SMC) techniques, the component-wise SMC approach offers several advantages, including improved decoupling of system dynamics, enhanced robustness, and greater flexibility in controller design. This paper proposes a novel trajectory tracking controller for a two-link manipulator based on the component-wise sliding mode control approach. The design methodology involves determining controller gains by solving a set of inequalities. This analysis results in conditions on the system parameter uncertainties that guarantee the existence of a feasible solution to the set of inequalities. Furthermore, an algorithm is presented to determine the maximum allowable uncertainties that ensure the feasibility of the controller gains. To evaluate the performance and robustness of the proposed tracking controller, the manipulator is subjected to a series of challenging trajectories, including circular and figure-8 ones, under both nominal and maximum allowable uncertainty conditions. The proposed controller demonstrates superior performance across both circular and figure-8 trajectories, exhibiting excellent transient response and minimal steady-state error even under the maximum permissible uncertainties, which extend up to 27% in link masses. This performance is validated through a quantitative analysis that incorporates a comparative evaluation against two conventional MIMO SMC techniques. The comparison is conducted using the Integral Norm of Error (INE) to assess tracking accuracy and the Integral Norm of Control Action (INU) to evaluate the energy efficiency of the controllers. These metrics provide a comprehensive basis for analyzing both the precision and the energy consumption of the proposed control strategy in relation to established methods.
Co-Authors Abdulla, Abdulla Ibrahim Mahmood, Saif S. Noaman, Mohanad N. Qasim, Mohammed Qasim, Mohammed Salim