Position control of servo motor systems is a challenging task because of inevitable factors such as uncertainties, nonlinearities, parametric variations, and external perturbations. In this article, to alleviate the above issues, a practical adaptive fast terminal sliding mode control (PAFTSMC) is proposed for better tracking performance of the servo motor system by using a state observer and bidirectional adaptive law. First, a smooth-tangent-hyperbolic-function-based practical fast terminal sliding mode control (PFTSM) surface is designed to ensure not only fast finite time tracking error convergence but also chattering reduction. Second, the PAFTSMC is proposed for the servo motor, in which a two-way adaptive law is designed to further suppress the chattering and overestimation problems. More importantly, the proposed adaptive technique can update the switching gain according to the system uncertainties, which can provide high gain in the reaching phase and then decrease to the smallest value in the sliding phase to avoid the monotonically increasing gain that exists in most adaptation methods. Third, the finite-time stability of the closed-loop system is proved based on the Lyapunov theorem. Finally, the simulation studies and experimental tests verify the effectiveness of the proposed control in terms of better tracking, strong robustness, and reduced chattering, compared to existing algorithms.
Objective: The objective of this study was to prepare nanosuspension of a practical water insoluble antiulcer drug which is lafutidine to enhance the solubility, dissolution rate with studying the effect of different formulation variables to obtain the best formula with appropriate physical properties and higher dissolution rate.Methods: Nanosuspension of lafutidine was prepared using solvent anti-solvent precipitation method using Polyvinylpyrrolidone K-90(PVP K-90) as the stabilizer. Ten formulations were prepared to show the effect of different variables in which two formulations showed the effect of stabilizer type, three formulations showed the effect of stabilizer concentration, two formulations showed the effect of combinatio
... Show MorePolycystic ovarian syndrome, additionally called PCOS is the most widespread endocrine illness amongst women. The aetiology of PCOS is attributed to a multi-factorial interplay among environmental and genetic effects. The overarching goal evaluates the correlation among blood concentrations of total testosterone, sex-hormone-binding globulin (SHBG), estradiol (E2), follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in ladies with PCOS and the impact of obesity, age, marital popularity on the obtained results. This study was conducted at the National Center for Educational Laborites /Medical City/ Baghdad. The study comprised of a sample of 83 women, elderly between 17 -45 years, who had been selected in a random manner
... Show MoreSelf-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab
... Show MoreWith the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev
... Show MoreResearchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
... Show MoreThe Caputo definition of fractional derivatives introduces solution to the difficulties appears in the numerical treatment of differential equations due its consistency in differentiating constant functions. In the same time the memory and hereditary behaviors of the time fractional order derivatives (TFODE) still common in all definitions of fractional derivatives. The use of properties of companion matrices appears in reformulating multilevel schemes as generalized two level schemes is employed with the Gerschgorin disc theorems to prove stability condition. Caputo fractional derivatives with finite difference representations is considered. Moreover the effect of using the inverse operator which tr
Accurate and correct price prediction of gold is significant to maintain the stability and fair operation of gold markets as well as the efficiency and proper functioning of financial markets related to gold trading. Gold prices have a long history of non-linear and non-stationary behavior that generates highly complex datasets which are very difficult to forecast with high accuracy and reliability. At the same time Support Vector Regression (SVR) has been utilized as a robust information for prediction not only gold prices but also overall metal price movements. First, the predictive capability of SVR is highly sensitive to hyperparameter selection which needs to be thoroughly tuned and optimized for potentially optimal performance. Theref
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