One of the main parts in hydraulic system is directional control valve, which is needed in order to operate hydraulic actuator. Practically, a conventional directional control valve has complex construction and moving parts, such as spool. Alternatively, a proposed Magneto-rheological (MR) directional control valve can offer a better solution without any moving parts by means of MR fluid. MR fluid consists of stable suspension of micro-sized magnetic particles dispersed in carrier medium like hydrocarbon oil. The main objectives of this present research are to design a MR directional control valve using MR fluid, to analyse its magnetic circuit using FEMM software, and to study and simulate the performance of this valve. In this research, a comprehensive literature review on the advancement of this technology provides valuable insight on MR valve design by previous researchers. The design of MR directional control valve, the construction of the valve and the principle of work are presented. The design of proposed MR single valve has enabled the development of the MR directional control valve. Design and finite elements analysis using FEMM software of the MR single valve and MR directional control valve were done to obtain the optimal design. The valve was fabricated and the experimental rig for valve test was developed. The experiment presentation for functional working principle of the valve and valve performance were shown. The results of the simulation results show that the valve works in controlling the direction and the speed of hydraulic actuators. The valve can be operated with variable flow rate by varying the electric current. It is found that the electric current is inversely proportional to the flow rate. High current produces low flow rate and vice versa. It does the work of the valves to proportionally control the hydraulic actuators. The valve can be operated as ON-OFF directional control valve as well as proportional directional control valve with meter-in or meter-out by changing electric connection.
This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
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Quality control charts are limited to controlling one characteristic of a production process, and it needs a large amount of data to determine control limits to control the process. Another limitation of the traditional control chart is that it doesn’t deal with the vague data environment. The fuzzy control charts work with the uncertainty that exists in the data. Also, the fuzzy control charts investigate the random variations found between the samples. In modern industries, productivity is often of different designs and a small volume that depends on the market need for demand (short-run production) implemented in the same type of machines to the production units. In such cases, it is difficult to determine the contr
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A 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
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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 m
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Find interested in the harmonization of variables and determinants of supply chain planning needs of the material, leading to the results start effective supply chain management, and end up quickly modify the sizes to suit the demand and turnover in the market. As well as identifying relationships between variables, and type of relationship used by the company with the processors and their feasibility, and indicate the level of interest and willingness to redesign the supply chain Company for Electrical Industries and build an integrated model for supply chain with the MRP system can be applied in the company.
Research depend on quantitative and descriptive method, It
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An innovative greenhouse which integrates a conventional greenhouse with roof mounted solar air heaters is used in this investigation. This design reduces the solar radiation incoming to the greenhouse in summer which reduced the load and cost of greenhouse cooling and provides a means of solar heating. Experimental measurements of the internal air and internal soil sub-layer temperatures in the greenhouse, without crops, were performed in Baghdad University, Baghdad, Iraq (33.3 °N, 44.4 °E). Measurements were recorded for clear and partly cloudy winter days. A dynamic model was developed to predict the all internal temperatures of the greenhouse. This model includes soil surface heat exchange with the greenhouse air which was found to gi
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