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.
Objective: To generate a model that conceptualizes the phenomenon of health promotion and its related factors.
Methodology: A grounded theory methodology is used as qualitative method to explore the health promotion as
phenomenon of interest and its other related factors from the perspectives of specialists in this field. The study is
carried out from January 2002 through September 2004. A sample of (20) specialists in health sciences are
selected and interviewed as experts in the area of health promotion. The investigators conducted intensive and
structured interviews with the specialists to collect the data. These interviews were transcribed verbatim,
analyzed and interpreted.
Results: Findings of the study indicat
As the bit rate of fiber optic transmission systems is increased to more than , the system will suffer from an important random phenomena, which is called polarization mode dispersion. This phenomenon contributes effectively to: increasing pulse width, power decreasing, time jittering, and shape distortion. The time jittering means that the pulse center will shift to left or right. So that, time jittering leads to interference between neighboring pulses. On the other hand, increasing bit period will prevent the possibility of sending high rates. In this paper, an accurate mathematical analysis to increase the rates of transmission, which contain all physical random variables that contribute to determine the transmission rates, is presen
... Show MoreDemography or population studies or demography is the science that is based on the different characteristics of the population scientific study, and represent a population studies principled way to understand the population of society, in addition to verification of the population in a given area determine the reason for the increase or decrease this number from the previous statistical As these studies estimate future trends for the occurrence of demographic change in terms of birth, death and migration That the registration of deaths of paramount importance narrated that way can the demographic reality of the population analysis, and coverage of the health authorities' needs and enable government institutions of decision-making
... Show MoreThe problem of internal sulfate attack in concrete is widespread in Iraq and neighboring countries.This is because of the high sulfate content usually present in sand and gravel used in it. In the present study the total effective sulfate in concrete was used to calculate the optimum SO3 content. Regression models were developed based on linear regression analysis to predict the optimum SO3 content usually referred as (O.G.C) in concrete. The data is separated to 155 for the development of the models and 37 for checking the models. Eight models were built for 28-days age. Then a late age (greater than 28-days) model was developed based on the predicted optimum SO3 content of 28-days and late age. Eight developed models were built for all
... Show MoreIn this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade
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