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A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot
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Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is more accurate in terms of fast on-line finding and tuning  parameters of the controller lead to obtaining smoothness with small spikes control action as well as minimizing tracking pose error of the wheeled mobile robot than the performance of nonlinear back-stepping technique.

 

Keywords: Bees Algorithm, Nonlinear Controller, Matlab Package, Particle Swarm Optimization, Wheeled Mobile Robots.

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Publication Date
Wed Mar 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Genetic –Based Face Retrieval Using Statistical Features
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Content-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In add

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Synthesis AgO Nanoparticles by Nd:Yag Laser with Different Pulse Energies
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     One technique used to prepare nanoparticles material is Pulsed Laser Ablation in Liquid (PLAL), Silver Oxide nanoparticles (AgO) were prepared by using  this technique, where silver target was submerged in ultra-pure water (UPW)  at room temperature after that Nd:Yag laser which characteristics by 1064 nm wavelength, Q-switched, and 6ns pulse duration was used to irradiated silver target. This preparation method was used to study the effects of laser irradiation on Nanoparticles synthesized by used varying laser pulse energy 1000 mJ, 500 mJ, and 100 mJ, with 500 pulses each time on the particle size. Nanoparticles are characterized using XRD, SEM, AFM, and UV-Visible spectroscopy. All the structural peaks determined by the XRD

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Science And Research (ijsr
Interaction of Alpha Particles with Breast Tissue
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As modern radiotherapy technology advances, radiation dose and dose distribution have improved significantly. As part of a natural evolution, there has recently been renewed interest in therapy, particularly in the use of heavy charged particles, because these types of radiation serve theoretical advantages in all biological and physical aspects. The interactions of alpha particle with matter were studied and the stopping powers of alpha particle with Breast Tissue were calculated by using Beth-Bloch equation, Zeigler's formula and SRIM software, also the Range and Liner Energy Transfer (LET) and Breast Thickness As well as Dose and Dose equivalent for this particle were calculated by using Mat lab language for (0.01-200) MeV alpha ene

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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Porous Silicon effect on the performance of CdS nanoparticles photodetector
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Cadmium sulfide photodetector was fabricated. The CdS nano
powder has been prepared by a chemical method and deposited as a
thin film on both silicon and porous p- type silicon substrates by spin
coating technique. Structural, morphological, optical and electrical
properties of the prepared CdS nano powder are studied. The X-ray
analysis shows that the obtained powder is CdS with predominantly
hexagonal phase. The Hall measurements show that the nano powder
is n-type with carrier concentration of about (-5.4×1010) cm-3. The
response time of fabricated detector was measured by illuminating
the sample with visible radiation and its value was 5.25 msec. The
specific detectivity of the fabricated det

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Optimization of nanostructured/nano sized rice husk ash preparation
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The 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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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi Method
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Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental Modeling and Optimization of Fatigue Life and Hardness of Carbon Steel CK35 under Dynamic Buckling
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Abstract

 

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

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In 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

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Engineering
Experimental Evaluation of the Strut-and-Tie Model Applied to Deep Beam with Near-Load Openings
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It is commonly known that Euler-Bernoulli’s thin beam theorem is not applicable whenever a nonlinear distribution of strain/stress occurs, such as in deep beams, or the stress distribution is discontinuous. In order to design the members experiencing such distorted stress regions, the Strut-and-Tie Model (STM) could be utilized. In this paper, experimental investigation of STM technique for three identical small-scale deep beams was conducted. The beams were simply supported and loaded statically with a concentrated load at the mid span of the beams. These deep beams had two symmetrical openings near the application point of loading. Both the deep beam, where the stress distribution cannot be assumed linear, and the ex

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Publication Date
Sat Dec 14 2019
Journal Name
International Journal On Emerging Technologies
Utilizing an Artificial Neural Network Model to Predict Bearing Capacity of Stone Columns
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ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

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