A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA). Matlab simulation package is used to carry out the proposed methodology that finds and tunes the optimal values of the robust PID parameters on-line. In real-time, the LabVIEW package is guided to design the on-line robust PID controller for the heating system. Numerical simulations and experimental results are compared with each other and showed the effectiveness of the proposed control methodology in terms of fast and smooth dynamic response for the heating system, especially when the control methodology considers the external disturbance attenuation problem.
The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Fol
... Show MoreIn real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson†and the “Expectation-Maximization†techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i
... Show MoreIn some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after
... Show MoreOur research comes to shed light on Iraqi literature as literature that arose in special circumstances alongside foreign literature. Using comparative research methods, we chose to highlight two distinguished writers, who have their mark in the world of literature. The first is the Iraqi writer Maysaloun Hadi, who is considered an icon of Iraqi feminist literature, and the second is the French writer Le Clézieu, who won the Nobel in 2008. We will see through the research how the two authors expressed their views of modernity and urbanism. And how each of them separately portrayed the psychological and moral projections that formed the essence of man today.
Résumé
Notre recherche abord un des points inc
... Show MoreIn the current endeavor, a new Schiff base of 14,15,34,35-tetrahydro-11H,31H-4,8-diaza-1,3(3,4)-ditriazola-2,6(1,4)-dibenzenacyclooctaphane-4,7-dien-15,35-dithione was synthesized. The new symmetrical Schiff base (Q) was employed as a ligand to produce new complexes comprising Co(II), Ni(II), Cu(II), Pd(II), and Pt(II) metal-ions at a ratio of 2:1 (Metal:ligand). There have been new ligands and their complexes validated by (FTIR), (UV-visible), 1H-NMR, 13C-NMR, CHNS, and FAA spectroscopy, Thermogravimetric analysis (TG), Molar conductivity, and Magnetic susceptibility. The photostabilization technique to enhance the polymer was also used. The ligand Q and its complexes were mixed in 0.5% w/w of polyvinyl chloride in tetrahydrofuran
... Show MoreВ статье рассматривается вопрос о связи флективных изменений с мыслительными процессами на материале русского и арабского языков, анализируются семантические, фонетические, морфологические и синтаксические основы фонограмматической когниции. Цель статьи выявление прямой связи между количественным звуковым изменением согласного состава слова и мыслительными процессами, с помощью которых человеческ
... Show MoreIn this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
... Show MoreAbstract
The aim of this paper is to model and optimize the fatigue life and hardness of medium carbon steel CK35 subjected to dynamic buckling. Different ranges of shot peening time (STP) and critical points of slenderness ratio which is between the long and intermediate columns, as input factors, were used to obtain their influences on the fatigue life and hardness, as main responses. Experimental measurements of shot peening time and buckling were taken and analyzed using (DESIGN EXPERT 8) experimental design software which was used for modeling and optimization purposes. Mathematical models of responses were obtained and analyzed by ANOVA variance to verify the adequacy of the models. The resul
... Show MoreThe Gray Wolf Optimizer (GWO) is a population-based meta-heuristic algorithm that belongs to the family of swarm intelligence algorithms inspired by the social behavior of gray wolves, in particular the social hierarchy and hunting mechanism. Because of its simplicity, flexibility, and few parameters to be tuned, it has been applied to a wide range of optimization problems. And yet it has some disadvantages, such as poor exploration skills, stagnation at local optima, and slow convergence speed. Therefore, different variants of GWO have been proposed and developed to address these disadvantages. In this article, some literature, especially from the last five years, has been reviewed and summarized by well-known publishers. Fir
... Show MoreThe objective of the study is developing a procedure for production and characterization of rice husk ash (RHA). The effects of rice husk (RH) amount, burning/cooling conditions combined with stirring on producing of RHA with amorphous silica, highest SiO2, lowest loss on ignition (LOI), uniform particle shape distribution and nano structured size have been studied. It is concluded that the best amount is 20 g RH in 125 ml evaporating dish Porcelain with burning for 2 h at temperature 700 °C combined with cooling three times during burning to produce RHA with amorphous silica, SiO2 90.78% and LOI 1.73%. On the other hand, cooling and stirring times affect the variation of nano structured size and particle shape dis
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