Real-Time Inverse Dynamic Deep Neural Network Tracking Control for Delta Robot Based on a COVID-19 Optimization

This paper presents a new technique to design an inverse dynamic model for a delta robot experimental setup to obtain an accurate trajectory. The input/output data were collected using an NI DAQ card where the input is the random angles profile for the three-axis and the output is the corresponding measured torques. The inverse dynamic model was developed based on the deep neural network (NN) and the new COVID-19 optimization to find the optimal initial weights and bias values of the NN model. Due to the system uncertainty and nonlinearity, the inverse dynamic model is not enough to track accurately the preselected profile. So, the PD compensator is used to absorb the error deviation of the end effector. The experimental results show that the proposed inverse dynamic deep NN with PD compensator achieves good performance and high tracking accuracy. The suggested control was examined using two different methods. The spiral path is the first, with a root mean square error of 0.00258 m, while the parabola path is the second, with a root mean square error of 0.00152 m

Proper maintenance way for the multifunctional windows

Recent developments have helped create windows that can fulfill their contrary functions effectively in addition to generating energy, which are known as multifunctional windows. Permanent maintenance is required for windows to achieve their functions properly, but the current window cleaning methods can harm and are not appropriate for the recently developed multifunctional windows. The author presents a suggested multifunctional window and sheds light on the disadvantages that could be accomplished when using the current methods to clean it. Using analytical and logical methods, this paper shows the proper way of the multifunctional window maintenance. This way depends on the self-cleaning features. The author proposes a solution for the disadvantages that could accompany that features. The main result is the validity of a successful multifunctional window that can be maintained with minimum disadvantages and maximum efficiency. Therefore, this study contributes to the window industry by presenting the proper way of maintaining multifunctional windows. Thus, future maintenance research should be redirected properly to conserve and benefit the efforts spent in impropriate directions and technologie

The Achievement Gap Between African American Athletes and Their White Counterparts in Higher Education

The achievement gap between African American athletes and their white counterparts is plaguing the United States. There are many reasons for the achievement gap. This synthesis will highlight the reasons while also discussing the solutions. To examine this matter to the fullest extent, there were 14 peer-reviewed articles chosen that talk about the reasons for the achievement gap. Several topics included in the articles were lack of role models and social supports, racial stereotypes, obsessive pursuit of sport goals, and the background of African American athletes. This synthesis will also discuss solutions to the achievement gap in collegiate athletics. These topics included funding, peer-to-peer mentoring, and credit-bearing courses

Network Optimization of Dynamically Complex Systems

The aim of this research is to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. As computers become more and more networked, it is easier to share files among storage media. In addition, more bandwidth will be consumed by network flow because customers will be connected through networks which will transfer files and data, such as video files (MPEGn, AVI, WMV, etc.) to be watched at a customer\u27s computer (host). Furthermore, these networks terminals will be used as mini warehouses to save files and data. Selective files will be transferred to the host computer depending on customers pre-requested profile and prioritization. The research will present techniques that optimize transfer storage media for the purpose of minimizing waiting time and hardware cost while maximizing efficiency and customer satisfaction

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID).

Improvement of common bean (Phaseolus vulgaris) nodulation by selected rhizobial strain from Egyptian soils through genotypic characterization, symbiotic effectiveness and competitiveness under salt stress conditions

To maximize the symbiotic nitrogen fixation of common bean (Phaseolus vulgaris) under egyptian soil conditions, twelve rhizobial isolates were isolated from root nodulated common bean. These isolates were physiologiacl characterized to test the more effeicient strains in nitrogen fixation, to select strains more adapted to environmetal stresses such as salinity, alkalinity, temperature. The adapted strains were selected to study the competitiveness of these strains against the standard strain CIAT 899 marked with gus gene under normal conditions, stress of salinity and stress of alkalinity. These strains were also characterized using molecular biology techniques such as REP-PCR, ARDRA of 16S and 23S rDNA, plasmid profiles analysis, sequencing of full length of 16S rDNA, hybridization with nifH gene and amplification of nodC gene. Strain EBRI 26 and Sinorhizobium meliloti strain 2010 were selected as salt tolerant strains to study the proteins involeved in salt tolerance by 2D proteom analysis and MALDI-Tof mass spectrometry

A New Self-Tuning Nonlinear PID Motion Control for One-Axis Servomechanism with Uncertainty Consideration

This paper introduces a new study for one-axis servomechanism with consideration the parameter variation and system uncertainty. Also, a new approach for high-performance self-tuning nonlinear PID control was developed to track a preselected profile with high accuracy. Moreover, a comparison study between the proposed control technique and the well-known controllers (PID and Nonlinear PID). The optimal control parameters were determined based on the COVID-19 optimization technique. The parameters of the servomechanism system changed randomly at a preselected range through the online simulation. The change of these parameters acts as the nonlinearity resources (friction, backlash, environmental effects) and system uncertainty. A comparative study between the linear and nonlinear models had been accomplished and investigated. The results show that the proposed controller can track several operating points with high accuracy, low rise time, and small overshoot

Downscaling extremes: A comparison of extreme value distributions in point-source and gridded precipitation data

There is substantial empirical and climatological evidence that precipitation extremes have become more extreme during the twentieth century, and that this trend is likely to continue as global warming becomes more intense. However, understanding these issues is limited by a fundamental issue of spatial scaling: most evidence of past trends comes from rain gauge data, whereas trends into the future are produced by climate models, which rely on gridded aggregates. To study this further, we fit the Generalized Extreme Value (GEV) distribution to the right tail of the distribution of both rain gauge and gridded events. The results of this modeling exercise confirm that return values computed from rain gauge data are typically higher than those computed from gridded data; however, the size of the difference is somewhat surprising, with the rain gauge data exhibiting return values sometimes two or three times that of the gridded data. The main contribution of this paper is the development of a family of regression relationships between the two sets of return values that also take spatial variations into account. Based on these results, we now believe it is possible to project future changes in precipitation extremes at the point-location level based on results from climate models.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS287 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model applied on egyptian load frequency control

This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of Egyptian load frequency control (ELFC). In this technique, the inputs to a TS Fuzzy model are the parameters of the change of operating points. The TS Fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDC-PID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed Optimal PID controller