Preferred Language
Articles
/
alkej-330
Solving the Inverse Kinematic Equations of Elastic Robot Arm Utilizing Neural Network
...Show More Authors

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinematic equation. To feed the neural network, experimental data were taken from an elastic robot arm for training the network, these data presented by joint angles, deformation variables and end-effector positions. The results of network training showed a good fit between the output results of the neural network and the targets data. In addition, this method for finding the inverse of kinematic equation proved its effectiveness and validation when applying the results of neural network practically in the robot’s operating software for controlling the real light robot’s position.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Fractional Brownian motion inference of multivariate stochastic differential equations
...Show More Authors

Recently, the financial mathematics has been emerged to interpret and predict the underlying mechanism that generates an incident of concern. A system of differential equations can reveal a dynamical development of financial mechanism across time. Multivariate wiener process represents the stochastic term in a system of stochastic differential equations (SDE). The standard wiener process follows a Markov chain, and hence it is a martingale (kind of Markov chain), which is a good integrator. Though, the fractional Wiener process does not follow a Markov chain, hence it is not a good integrator. This problem will produce an Arbitrage (non-equilibrium in the market) in the predicted series. It is undesired property that leads to erroneous conc

... Show More
Scopus (4)
Scopus
Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Power Generation from Utilizing Thermal Energy of Hazardous Waste Incinerators
...Show More Authors

A large amount of thermal energy is generated from burning hazardous chemical wastes, and the temperature of the flue gases in hazardous waste incinerators reaches up to (1200 °C). The flue gases are cooled to (40°C) and are treated before emission. This thermal energy can be utilized to produce electrical power by designing a system suitable for dangerous flue gases in the future depending on the results of much research about using a proto-type small steam power plant that uses safe fuel to study and develop the electricity generation process with water tube boiler which is manufactured experimentally with theoretical development for some of its parts which are inefficient in experimental work. The studied system gen

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Fri Aug 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Effects of utilizing Crumb Rubber as Aggregate in Asphalt Mixtures
...Show More Authors

Experts have given much attention on the use of waste in asphalt paving because of its significance from a sustainability perspective. This paper evaluated the performance properties of asphalt concrete mixes modified with Crumb Rubber (CR) as a partial replacement for two grade sizes of fine aggregate (2.36, and 0.3 mm) at six replacement rates: 0%, 2%, 4%, 6%, 8%, and 10% by weight. Asphalt concrete mixes were prepared at their Optimum Asphalt Content (OAC) and then tested for their engineering properties. Marshall properties, fatigue, rutting, ideal CT index test, Scanning Electron Microscopy (SEM), and Energy-Dispersive X-ray (EDX) spectroscopy were deployed to examine the crystalline structure and elemental composition of the C

... Show More
View Publication
Scopus (4)
Crossref (3)
Scopus Crossref
Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Experimental Investigation Utilizing Thermal Image Technique to the Heat Transfer Enhancement Using Oscillated Fins
...Show More Authors

Heat transfer around a flat plate fin integrated with piezoelectric actuator used as oscillated fin in laminar flow has been studied experimentally utilizing thermal image camera. This study is performed
for fixed and oscillated single and triple fins. Different substrate-fin models have been tested, using fins of (35mm and 50mm) height, two sets of triple fins of (3mm and 6mm) spacing and three frequencies
applied to piezoelectric actuator (5, 30 and 50HZ). All tests are carried out for (0.5 m/s and 3m/s) in subsonic open type wind tunnel to evaluate temperature distribution, local and average Nusselt number (Nu) along the fin. It is observed, that the heat transfer enhancement with oscillation is significant compared to without o

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Physics: Conference Series
The operational matrices for Elliptic Partial Differential Equations with mixed boundary conditions
...Show More Authors
Abstract<p>The purpose of this research is to implement the orthogonal polynomials associated with operational matrices to get the approximate solutions for solving two-dimensional elliptic partial differential equations (E-PDEs) with mixed boundary conditions. The orthogonal polynomials are based on the Standard polynomial (<italic>x<sup>i</sup> </italic>), Legendre, Chebyshev, Bernoulli, Boubaker, and Genocchi polynomials. This study focuses on constructing quick and precise analytic approximations using a simple, elegant, and potent technique based on an orthogonal polynomial representation of the solution as a double power series. Consequently, a linear </p> ... Show More
View Publication
Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
...Show More Authors

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

... Show More
View Publication Preview PDF
Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solution of Second Kind Volterra Integral Equations Using Non-Polynomial Spline Functions
...Show More Authors

In this paper we use non-polynomial spline functions to develop numerical methods to approximate the solution of 2nd kind Volterra integral equations. Numerical examples are presented to illustrate the applications of these method, and to compare the computed results with other known methods.

View Publication Preview PDF
Crossref
Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
...Show More Authors

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Fri Aug 30 2024
Journal Name
Iraqi Journal Of Science
A fourth Order Pseudoparabolic Inverse Problem to Identify the Time Dependent Potential Term from Extra Condition
...Show More Authors

     In this work, the pseudoparabolic problem of the fourth order is investigated to identify the time -dependent potential term under periodic conditions, namely, the integral condition and overdetermination condition. The existence and uniqueness of the solution to the inverse problem are provided. The proposed method involves discretizing the pseudoparabolic equation by using a finite difference scheme, and an iterative optimization algorithm to resolve the inverse problem which views as a nonlinear least-square minimization. The optimization algorithm aims to minimize the difference between the numerical computing solution and the measured data. Tikhonov’s regularization method is also applied to gain stable results. Two

... Show More
View Publication
Scopus (2)
Crossref (3)
Scopus Crossref
Publication Date
Mon Nov 14 2022
Journal Name
Physica Scripta
A wavelet-based collocation technique to find the discontinuous heat source in inverse heat conduction problems
...Show More Authors
Abstract<p>This paper is devoted to an inverse problem of determining discontinuous space-wise dependent heat source in a linear parabolic equation from the measurements at the final moment. In the existing literature, a considerably accurate solution to the inverse problems with an unknown space-wise dependent heat source is impossible without introducing any type of regularization method but here we have to determine the unknown discontinuous space-wise dependent heat source accurately using the Haar wavelet collocation method (HWCM) without applying the regularization technique. This HWCM is based on finite-difference and Haar wavelets approximation to the inverse problem. In contrast to othe</p> ... Show More
View Publication
Scopus (20)
Crossref (18)
Scopus Clarivate Crossref