saad jabbar abbas
@ruc.edu.iq
Computer Techniques Engineering
Al-Rafidain University College
EDUCATION
ME in electronics instrumentation and control, Thapar University (India) 2012.
B.Sc. in electric engineering, Al-Mustansirya University 2003.
RESEARCH INTERESTS
Control System
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ammar Al-Jodah, Saad Jabbar Abbas, Alaq F. Hasan, Amjad J. Humaidi, Abdulkareem Sh. Mahdi Al-Obaidi, Arif A. AL-Qassar, and Raaed F. Hassan
Akademiai Kiado Zrt.
AbstractThe demand for automation using mobile robots has been increased dramatically in the last decade. Nowadays, mobile robots are used for various applications that are not attainable to humans. Omnidirectional mobile robots are one particular type of these mobile robots, which has been the center of attention for their maneuverability and ability to track complex trajectories with ease, unlike their differential type counterparts. However, one of the disadvantages of these robots is their complex dynamical model, which poses several challenges to their control approach. In this work, the modeling of a four-wheeled omnidirectional mobile robot is developed. Moreover, an intelligent Proportional Integral Derivative (PID) neural network control methodology is developed for trajectory tracking tasks, and Particle Swarm Optimization (PSO) algorithm is utilized to find optimized controller's weights. The simulation study is conducted using Simulink and Matlab package, and the results confirmed the accuracy of the proposed intelligent control method to perform trajectory tracking tasks.
Amjad Jaleel Humaidi, Ahmed A. Oglah, Saad Jabbar Abbas, and Ibraheem K. Ibraheem
Praise Worthy Prize
This article presents the optimal control design for trajectory tracking of Delta\\Par4-like parallel manipulator controlled by two augmented control schemes: Augmented PD Controller (APD) and Augmented Nonlinear PD (ANPD) Controller. Firstly, the Particle Swarm Optimization (PSO) technique is employed for optimal tuning of design parameters for each control structure in order to reach better dynamic performance. Then, two comparisons are made in order to evaluate the performance of parallel robot based on optimized ANPD and APD controllers. The first comparison is established in terms of tracking error accuracy due to the involved controllers, while the other one is based on the strength of robustness granted by each controller against variation of parallel robot parameters. The verification of performance comparisons is made via simulation within the environment of MATLAB/Simulink programming platform. The circular path is used for performance evaluation of controllers for trajectory tracking control. The simulated results have showed that ANPD controller outperforms the APD controller in terms of tracking accuracy and robustness.