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International Review of Applied Sciences and Engineering
Authors:
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

that involves the proposed control methodology is shown in Fig. 2 . The error between the reference and actual position is multiplied by the orthogonal rotational matrix to transfer the error from the world coordinates to the robot coordinates. The PSO

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error value. It is essential to adjust the PID parameters to obtain the desired output. For this purpose, various optimization algorithms are used. One of them is particle swarm optimization (PSO) [ 1 , 2 ]. PID is used in many applications such as

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by PSCs [ 17 ]. However, the development of MPPT controllers has also made use of optimization techniques that are based on swarm intelligence (SI) [ 18 , 19 ], like ant colony optimization (ACO) and particle swarm optimization (PSO) [ 20 , 21

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inverse kinematics (IK) of a 3-DOF redundant manipulator robot. Batista et al. [ 15 ] used Least Squares (LS), Recursive Least Square (RLS), and dynamic parameter identification algorithm based on Particle Swarm Optimization (PSO) with search space defined

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Optimization (PSO); Ant Colony Optimization (ACO.); and Genetic Algorithm (GA); are commonly employed (GA). Despite its advantages over other artificial intelligence algorithms, as demonstrated by the results of this research, the SSO is rarely employed to

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-copter. ❑ Conducting a comparative study between SHO and PSO algorithms in terms of dynamic performance and robustness characteristics. The rest of the article is arranged as follows: Section 2 developed the mathematical model of Tri-copter. Section 3 presents the

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by congestion [ 6 ]. Nodal pricing, FACTS-based CM, ATC-based CM, and price area CM methods are coming under conventional CM methods. The computational time is more in Conventional CM methods compared to heuristic optimization methods. PSO, GA, BFA

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], particle swarm optimization (PSO) [ 20 ], and Grey-wolf optimization [ 21 ] are examples of common optimization methods that are given and used in exoskeleton devices. Algorithm for ant colony optimization [ 22 ] was also used. GA is easy to use and capable

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to be approximated by H BP and k is the coefficients (k 1 , k 2 , k 3 ) of FO BPF function given in (4) . Fig. 2. Flow Chart of the bi-level PSO algorithm

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techniques such as Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Butterfly Optimization Algorithm (BOA), and Gray Wolf Optimization (GWO) to tune the design parameters of the proposed observer for further improvement [ 28

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