Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’Alembert principle. Secondly, an adaptive robust controller, based on a sliding mode, is designed to manipulate the problem of uncertainties, including modeling errors. Last, a higher stability controller, based on the RBF neural network, is implemented with the adaptive robust controller to stabilize the ARAs, avoiding modeling errors and unknown payload issues. The novelty of the proposed design is that it takes into account high nonlinearities, coupling control loops, high modeling errors, and disturbances due to payloads and environmental conditions. The model was evaluated by the simulation of a case study that includes the two proposed controllers and ARA trajectory tracking. The simulation results show the validation and notability of the presented control algorithm.
The research aims to identify the psychological and health risks that a child might be exposed to by playing with hazardous toys such as pellet guns. To this end, the researcher has visited Ibn Al-Haytham Eye Hospital in Baghdad, the emergency department to figure out the rate of injuries in Children for the consecutive years (2017-2018) and the first Month of (2019). The psychological risks as a result of disability are represented by the inability to accommodate the surrounding environment well. Additionally, the child experiences a kind of tension, conflict, and going in psychological crises through introversion, isolation, withdrawal tendencies, and poor conformity with himself and the Society.
The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
... Show MoreReceipt Date:10/11/2021 Acceptance Date:29/12/2021 Publication Date:31/12/2021
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The study aimed to clarify the conceptual explanations and the theoretical rooting of the concept of the populist phenomenon. And explore the political and cultural implications and connotations contained in populist political discourse. And to stand on the foundations and meanings on w
... Show MoreThe research is exposed to the concept of rough discourse in contemporary theater with a critical reading that takes the genealogical work as a starting point in deconstructing the references of rough discourse and pursuing its paths in the civilization and cultural framework and how it identifies aesthetically within the theatrical field and the extents of its procedural treatments in order to reveal it and clarify its limits and representations, as the research included the first chapter. (methodological framework), the second chapter (theoretical framework), which included two sections, the first took place under the title (rough dramatization), while the second topic took place under the title (rough drama), and the second chapter re
... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien
... Show MoreThis study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, th
... Show MoreThis study revolves around the rapid changes of science and a comparison of the formal and practical aspects and the reason behind summoning the changes and their types, which are subject to the influence of the recipient. This transformation represents formal and intellectual production cycles and formal functional generation that is subject to the goals of the system of multiple differences at the level of time and place. It meets the needs and the request for change, but access to it comes through multiple systems and portals that are different from the normal and the usual, so this study was called (meta and its dimensions in the designed biological formation (virtual reality environment - a model). The research seeks to find solutio
... Show MoreThis paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.