This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; this is demonstrated by the minimized tracking error and obtained smoothness of the velocity control signal, especially when external disturbances are applied.
This study aims to highlight the role of strategic leadership in adopting the intelligent organization model. The study was conducted on 7 economic organizations in Algeria. The study population consisted of 354 leaders, of whom a random sample of 176 leaders (managers, department heads, division heads, engineers) was selected. The researcher used a questionnaire as the main tool of the study. Statistical analysis and hypothesis testing were conducted using SEM (Structural Equation Modeling) with the aid of SPSS.v26 and AMOS.v24 software. The study concluded with a set of results, most notably: there is a statistically significant direct positive effect between strategic leadership and building intelligent organizations at a significance le
... Show MoreBased on nonlinear self- diffraction technique, the nonlinear optical properties of thin slice of matter can be obtained. Here, nonlinear characterization of nano-fluids consist of hybrid Single Wall Carbon Nanotubes and Silver Nanoparticles (SWCNTs/Ag-NPs) dispersed in acetone at volume fraction of 6x10-6, 9x10-6, 18x10-6 have been investigated experimentally. Therefore, CW DPSS laser at 473 nm focused into a quartz cuvette contains the previous nano-fluid was utilized. The number of diffraction ring patterns (N) has been counted using Charge - Coupled- Device (CCD) camera and Pc with a certain software, in order to find the maximum change of refractive index ( of fluids. Our result show that the fraction volume of 18x10-6 is more nonli
... Show MoreThe flexible joint robot manipulators provide various benefits, but also present many control challenges such as nonlinearities, strong coupling, vibration, etc. This paper proposes optimal second order integral sliding mode control (OSOISMC) for a single link flexible joint manipulator to achieve robust and smooth performance. Firstly, the integral sliding mode control is designed, which consists of a linear quadratic regulator (LQR) as a nominal control, and switching control. This control guarantees the system robustness for the entire process. Then, a nonsingularterminal sliding surface is added to give a second order integral sliding mode control (SOISMC), which reduces chartering effect and gives the finite time convergence as well. S
... Show MoreIn the present work, different thicknesses of CdS film were prepared by chemical bath deposition. Z-Scan technique was used to study the nonlinear refractive index and nonlinear absorption coefficients. Linear optical testing were done such as transmission test, and thickness of films were done by the interference fringes (Michelson interferometer). Z-scan experiment was performed at 650nm using CW diode laser and at 532nm wavelength. The results show the effect of self-focusing and defocusing that corresponds with nonlinear refraction n2. The effect of two-photon absorption was also studied, which correspond to the nonlinear absorption coefficient B.
This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The
... Show MoreSeeking pharmacist advice about minor ailments is a common practice among Iraqi patients because such advice is free and quick. Unfortunately, the assessment and management of minor ailments by Iraqi pharmacists were inappropriate. Therefore, this study aimed to develop a model for a mobile application that can assist community pharmacists in the diagnosis and management of minor ailments.
The scientific content of the application was based on the information in the symptoms in the pharmacy and British Nati
An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co
... Show MoreThis research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f
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