The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce chattering based on two-state observers with no requirements of the velocity and acceleration measurements in the FJR system. Furthermore, an adaptive laws for switching gains are proposed for both slow and fast subsystems in the FJR to remove the requirements of knowing the up-bound of the disturbances and uncertainties. The closed loop stability of not only slow and fast subsystems but also the overall FJR is proved using the Lyapunov theorem. Finally, the simulation and experimental results demonstrate the superiority of proposed control in terms of less tracking error, significant noise suppression, and strong robustness in comparison with existing controllers.
The present study discusses the problem based learning in Iraqi classroom. This method aims to involve all learners in collaborative activities and it is learner-centered method. To fulfill the aims and verify the hypothesis which reads as follow” It is hypothesized that there is no statistically significant differences between the achievements of Experimental group and control group”. Thirty learners are selected to be the sample of present study.Mann-Whitney Test for two independent samples is used to analysis the results. The analysis shows that experimental group’s members who are taught according to problem based learning gets higher scores than the control group’s members who are taught according to traditional method. This
... Show MoreA new series of N-acyl hydrazones (4a-g) derived from indole-3-propionic acid (IPA) were synthesized. These N-acyl hydrazones were prepared by the reaction of 3-(1H-indol-3-yl) propane hydrazide and aldehyde in the existence of glacial acetic acid as a catalyst. 1HNMR and FT-IR analyses were used to identify the synthesized compounds and they were in vitro evaluated as antibacterial agents against six different types of microorganisms by using well diffusion method. All the tested N-acyl hydrazones (4a-g) displayed moderate activity against the Gram-negative E.coli, comparable to that of Amoxicillin. Some of the tested N-acyl hydrazones also exhibited intermediate activity ag
... Show MoreA hybrid cadmium sulfide nanoparticles (CdSNPs) electroluminescence (EL) device was fabricated by Phase – Segregated Method and characterized. It was fabricated as layers of (ITO/poly-TPD:CdS ) and (ITO/poly-TPD:CdS /Alq3). Poly-TPD is an excellent Hole Transport Layer (HTL), CdSNPs is an emitting layer and Alq3 as electron transport layer (ETL). The EL of Organic-Inorganic Light Emitting Diode (OILED) was studied at room temperature at 26V. This was achieved according to band-to-band transition in CdSNPs. From the I-V curve behavior, the addition of Alq3 layer decreased the transfer of electrons by about 250 times. The I-V behavior for (poly-TPD/CdS) is exponential with a maximum current of 4500 µA. While, the current i
... Show MoreThe second leading cause of death and one of the most common causes of disability in the world is stroke. Researchers have found that brain–computer interface (BCI) techniques can result in better stroke patient rehabilitation. This study used the proposed motor imagery (MI) framework to analyze the electroencephalogram (EEG) dataset from eight subjects in order to enhance the MI-based BCI systems for stroke patients. The preprocessing portion of the framework comprises the use of conventional filters and the independent component analysis (ICA) denoising approach. Fractal dimension (FD) and Hurst exponent (Hur) were then calculated as complexity features, and Tsallis entropy (TsEn) and dispersion entropy (DispEn) were assessed as
... Show MoreThe present study investigates deep eutectic solvents (DESs) as potential media for enzymatic hydrolysis. A series of ternary ammonium and phosphonium-based DESs were prepared at different molar ratios by mixing with aqueous glycerol (85%). The physicochemical properties including surface tension, conductivity, density, and viscosity were measured at a temperature range of 298.15 K – 363.15 K. The eutectic points were highly influenced by the variation of temperature. The eutectic point of the choline chloride: glycerol: water (ratio of 1: 2.55: 2.28) and methyltriphenylphosphonium bromide:glycerol:water (ratio of 1: 4.25: 3.75) is 213.4 K and 255.8 K, respectively. The stability of the lipase enzyme isolated from porcine pancreas (PPL) a
... Show MoreIron–phthalocyanine (FePc) organic photoconductive detector was fabricated using pulsed laser deposition (PLD) technique to work in ultraviolet (UV) and visible regions. The organic semiconductor material (iron phthalocyanine) was deposited on n-type silicon wafer (Si) substrates at different thicknesses (100, 200 and 300) nm. FePc organic photoconductive detector has been improved by two methods: the first is to manufacture the detector on PSi substrates, and the second is by coating the detector with polyamide–nylon polymer to enhance the photoconductivity of the FePc detector. The current–voltage (I–V) characteristics, responsivity, photocurrent gain, response time and the quantum efficiency of the fabricated photoconduc
... Show MoreCybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the
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