sensor sampling rate (SSR) may be an effective and crucial field in networked control systems. Changing sensor sampling period after designing the networked control system is a critical matter for the stability of the system. In this article, a wireless networked control system with multi-rate sensor sampling is proposed to control the temperature of a multi-zone greenhouse. Here, a behavior based Mamdany fuzzy system is used in three approaches, first is to design the fuzzy temperature controller, second is to design a fuzzy gain selector and third is to design a fuzzy error handler. The main approach of the control system design is to control the input gain of the fuzzy temperature controller depending on the current zone and current sensor rate for each zone. Due to the low input gain of the fuzzy controller, the steady state output error of the greenhouse temperature is in the range (0.55 – 11.22) % when the system using five sensors of different sampling rates and in the range (2.43 - 16.74) % when the system using five sensors with the same sampling rates. Next, after designing the fuzzy error handler, this error doesn’t exceed 1.6%, but in most cases it is less than 0.15%.The work is Simulink designed and implemented using Matlab R2012b. The Zigbee wireless network is proposed for the system, it is implemented in Matlab using True time 2.0 library.
In this paper, experimental study has been done for temperature distribution in space conditioned with Ventilation Hollow Core Slab (TermoDeck) system. The experiments were carried out on a model room with dimensions of (1m 1.2m 1m) that was built according to a suitable scale factor of (1/4). The temperature distributions was measured by 59 thermocouples fixed in several locations in the test room. Two cases were considered in this work, the first one during unoccupied period at night time (without external load) and the other at day period with external load of 800W/m2 according to solar heat gain calculations during summer season in Iraq. All results confirm the use of TermoDeck system for ventilation and cooling/heat
... Show MoreAbstract
Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance. This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H2/H∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS). Simulatio
... Show MoreA perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca
... Show MorePathological blood clot in blood vessels, which often leads to cardiovascular diseases, are one of the most common causes of death in humans. Therefore, enzymatic therapy to degrade blood clots is vital. To achieve this goal, bromelain was immobilized and used for the biodegradation of blood clots. Bromelain was extracted from the pineapple fruit pulp (Ananas comosus) and purified by ion exchange chromatography after precipitation with ammonium sulphate (0-80 %), resulting in a yield of 70%, purification fold of 1.42, and a specific activity of 1175 U/mg. Bromelain was covalently immobilized on functionalized multi-walled carbon nanotubes (MWCNT), with an enzyme loading of 71.35%. The results of the characterization of free and immobilized
... Show MoreBackground: Acute appendicitis is the most common abdominal surgical emergency. The diagnosis of this condition is still essentially clinical and there is difficulty in the clinical diagnosis, especially among elderly, children and patients with a typical presentation, so early and accurate diagnosis of acute appendicitis is important to avoid its complications.Objectives: To evaluate the degree of accuracy of Alvarado scoring system in the diagnosis of acute appendicitis.Method: Two hundred patients were admitted to the Alkindy Teaching Hospital from January 2011 to april 2014- presented with symptoms and signs suggestive of acute appendicitis. After examination and investigations all patients were given a score according to Alvarado sc
... Show MoreOver the past few decades, the health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to the emergence of drug-resistant bacteria. The clinical use of a combination of antibiotic therapy for Pseudomonas aeruginosa infections is probably more effective than monotherapy. The present study aims to estimate the antibacterial and antibiofilm activity of Conocarpus erectus leaves extracts against multi-drug resistant P. aeruginosa isolated from different hospitals in Baghdad city. One hundred fifty different clinical specimens were collected from patients from September 2021 to January 2022. All samples were
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show More