Astronomers have known since the invention of the telescope that atmospheric turbulence affects celestial images. So, in order to compensate for the atmospheric aberrations of the observed wavefront, an Adaptive Optics (AO) system has been introduced. The AO can be arranged into two systems: closedloop and open-loop systems. The aim of this paper is to model and compare the performance of both AO loop systems by using one of the most recent Adaptive Optics simulation tools, the Objected-Oriented Matlab Adaptive Optics (OOMAO). Then assess the performance of closed and open loop systems by their capabilities to compensate for wavefront aberrations and improve image quality, also their effect by the observed optical bands (near-infrared band

      In this research, a variable stiffness actuator is proposed to enhance the damping of the mechanical vibrating system. The frequency response analysis of the vibrating system is dependant in order to analyze and synthesis this semi-active damping, where the suggested process is using active filter to estimate the present frequency of the vibration system, and this will limit the value of the stiffness of the vibrated system. Two active filter s are needed, low-pass-filter (LPF) to choose the higher stiffness of the actuator at small frequencies as well as more damping and high-pass-filter (HPF) to choose the lower stiffness of the actuator at high frequencies as well as more damping, and so

Joint dysfunction disables are impacting millions of individuals worldwide. It significantly interferes with essential daily tasks like eating, drinking, and writing, often making self-care challenging for those affected. Exoskeleton robots are developed to enable individuals with impaired physical functions to perform daily activities and maintain independence. This study introduces a wearable exoskeleton control system for the elbow joint designed, providing an alternative assistive solution to traditional treatment methods. The elbow exoskeleton system used for therapy has nonlinearity and time-dependent parameters. To address these challenges, this work presents a sliding mode control (SMC) for tracking the path of an EES. To reduce the

Recently, Knowledge Management Systems (KMS) consider one of the major fields of study in educational institutions, caused by the necessity to identify their knowledge value and success. Hence, based on the updated DeLone and McLean’s Information Systems Success Model (DMISSM), this study set out to assess the success of the Perceived Usefulness of Knowledge Management Systems (PUKMS) in Iraqi universities. To achieve this objective, the quantitative method is selected as the research design. In total, 421 university administration staff members from 13 Iraqi private universities were conducted. This study highlights a number of significant results depending on structural equation modeling which confirms that system, information, and s

In this article, a continuous terminal sliding mode control algorithm is proposed for servo motor systems. A novel full-order terminal sliding mode surface is proposed based on the bilimit homogeneous property, such that the sliding motion is finite-time stable independent of the system’s initial condition. A new continuous terminal sliding mode control algorithm is proposed to guarantee that the system states reach the sliding surface in finitetime. Not only the robustness is guaranteed by the proposed controller but also the continuity makes the control algorithm more suitable for the servo mechanical systems. Finally, a numerical example is presented to depict the advantages of the proposed control algorithm. An application in the rota

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).