Szerző szerinti böngészés "Humaidi, Amjad J."

Megjelenítve 1 - 3 (Összesen 3)
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    Adaptive backstepping control design for ball and beam system
    (Akadémiai Kiadó, 2021-12) Al-Dujaili, Ayad Q.; Humaidi, Amjad J.; Pereira, Daniel Augusto; Ibraheem, Ibraheem Kasim; nem
    Ball and Beam system is one of the most popular and important laboratory models for teaching control systems. This paper proposes a new control strategy to the position control for the ball and beam system. Firstly, a nonlinear controller is proposed based on the backstepping approach. Secondly, in order to adapt online the dynamic control law, adaptive laws are developed to estimate the uncertain parameters. The stability of the proposed adaptive backstepping controller is proved based on the Lyapunov theorem. Simulated results are presented to illustrate the performance of the proposed approach.
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    Optimum of fractional order fuzzy logic controller with several evolutionary optimization algorithms for inverted pendulum
    (Akadémiai Kiadó, 2023-02-13) Ghaleb, A.F.; Oglah , Ahmed Alaa; Humaidi, Amjad J.; Al-Obaidi, Abdulkareem Sh. Mahdi; Ibraheem, Ibraheem Kasim; Al-Obaidi, Abdulkareem Sh. Mahdi; nem
    This paper compared the performance between Integer Order Fuzzy PID (IOFPID) and Fractional Order Fuzzy PID (FOFPID) controllers for inverted pendulum system as a controlling plant. The parameters of each controller were tuned with four evolutionary optimization algorithms (Social Spider Optimization (SSO), Swarm Optimization (PSO), Genetic Algorithm (GA), and Particle Ant Colony Optimization (ACO)). The comparisons were carried out between the two controllers IOFPID and FOFPID, as well as among the four optimization algorithms for the two controllers. The results of comparisons proved that the FOFPID controller with SSO has achieved the best time response char- acteristics and the least tuning time.
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    PSO-based optimized neural network PID control approach for a four wheeled omnidirectional mobile robot
    (Akadémiai Kiadó, 2023-02-13) Al-Jodah, Ammar; Abbas, Saad Jabbar; Hasan, Alaq F.; Humaidi, Amjad J.; Mahdi Al-Obaidi, Abdulkareem Sh.; Al-Qassar, Arif A.; Hassan, Raaed F.; nem
    The 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. Omni- directional 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 ac- curacy of the proposed intelligent control method to perform trajectory tracking tasks