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.
Poets of the age since ancient times to recount the events of their adventures in a fun story style in which the elements of the story of personalities, time and place, and we do not mean this modern art technique (poetic story) as it is now, but was aimed at the pleasures of the other receiving because it is the rule of the quality of literary output, Other times the narrative of events inspired by his broad imagination and this mixing indicates the story's involvement with Arabic poetry to be (poetic story) and this depends entirely on addressing the poet to the recipient, and requires in this narrative to be familiar with the elements of influence and suspense in the other or turned into a monotonous and dull narrative Influential, un
... Show MoreIn this research The study of Multi-level model (partial pooling model) we consider The partial pooling model which is one Multi-level models and one of the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly among the stations in Iraq. We use Akaik′s Informa
... Show MoreIn this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req
... Show MoreThis research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro
... Show MoreWhen exercising their authority in the jurisprudence, judges are subject to a set of restrictions that they must adhere to, as they do not want their jurisprudence to be accepted and welcomed by law practitioners in general, and legal scholars in particular, and in contrast to it, the arrows of criticism and defamation will extend to that jurisprudence, and then they will have to reverse them . Perhaps the most important of those restrictions imposed on judges is their observance of justice between the parties to the lawsuit through their lack of bias for one of the parties at the expense of the other, in addition to their observance of public order and public morals, as well as their observance of the legal texts that they work under its u
... Show MoreVarious simple and complicated models have been utilized to simulate the stress-strain behavior of the soil. These models are used in Finite Element Modeling (FEM) for geotechnical engineering applications and analysis of dynamic soil-structure interaction problems. These models either can't adequately describe some features, such as the strain-softening of dense sand, or they require several parameters that are difficult to gather by conventional laboratory testing. Furthermore, soils are not completely linearly elastic and perfectly plastic for the whole range of loads. Soil behavior is quite difficult to comprehend and exhibits a variety of behaviors under various circumstances. As a result, a more realistic constitutive model is
... Show MoreIn this paper, a harvested prey-predator model involving infectious disease in prey is considered. The existence, uniqueness and boundedness of the solution are discussed. The stability analysis of all possible equilibrium points are carried out. The persistence conditions of the system are established. The behavior of the system is simulated and bifurcation diagrams are obtained for different parameters. The results show that the existence of disease and harvesting can give rise to multiple attractors, including chaos, with variations in critical parameters.
This present paper aim at knowing the process of evaluating the training program that could be applied in Maysan Health office for it significance and importance in field of management and vocational staff preparations of high scientific experience in different fields of Health. The society of research includes staffs working in Maysan Health Office , of specialists , dentists, pharmacists, laboratories, nursing and administrators. Their number is 100 employees, the researcher has designed questionnaire by depending on "Kirkpatrick" for assessing the training . The researcher has used thorough survey and has entailed 90 questionnaire,
... Show More