Year:

  1.  62
    Temperature Control of a Steam Condenser Using NARMA-L2 Controller.Mustefa Jibril, Mesay Tadesse & Nuriye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (10):318-323.
    This study investigates the outlet temperature control for the design of steam condenser. The comparison has been made for a step drop in the steam condenser temperature set point using MATLAB/ Simulink environment for the steam condenser with NARMA-L2 using Levenberg-Marquardt algorithm and NARMA-L2 using resilient backpropagation algorithm controllers. The steam condenser with NARMA-L2 using Levenberg-Marquardt algorithm controller presented excellent and superior dynamic performance in response to the temperature drop in settling time. The overall simulation results demonstrated that the steam (...)
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  2.  97
    Inverted Pendulum Control Using NARMA-L2 with Resilient Backpropagation and Levenberg Marquardt Backpropagation Training Algorithm.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (10):324-330.
    In this study, the performance of inverted pendulum has been Investigated using neural network control theory. The proposed controllers used in this study are NARMA-L2 with Resilient backpropagation and Levenberg Marquardt backpropagation algorithm controllers. The mathematical model of Inverted Pendulum on a Cart driving mechanism have been done successfully. Comparison of an inverted pendulum with NARMA-L2 with Resilient backpropagation and Levenberg Marquardt backpropagation algorithm controllers for a control target deviation of an angle from vertical of the inverted pendulum using two (...)
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  3.  30
    Comparison of Neural Network NARMA-L2 Model Reference and Predictive Controllers for Electromagnetic Space Vehicle Suspension System.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (10):313-317.
    Electromagnetic Suspension System (EMS) is mostly used in the field of high-speed vehicle. In this study, a space exploring vehicle quarter electromagnetic suspension system is modelled, designed and simulated using Neural network-based control problem. NARMA-L2, Model reference and predictive controllers are designed to improve the body travel of the vehicle using bump road profile. Comparison between the proposed controllers is done and a promising simulation result have been analyzed.
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  4. Nonlinear Active Suspension System Control Using Fuzzy Model Predictive Controller.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (9):289-295.
    Recent years, active suspension system has been widely used in automobiles to improve the road holding ability and the riding comfort. This study presents a new fuzzy model predictive control for a nonlinear quarter car active suspension system. A nonlinear dynamical model of active suspension is established, where the nonlinear dynamical characteristic of the spring and damper are considered. Based on the proposed fuzzy model predictive control method is presented to stabilize the displacement of the active suspension in the presence (...)
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  5.  59
    Automatic Heat Dispel System for DINGSON Biscuit Oven Using Thermocouple Temperature Sensor.Mustefa Jibril - 2021 - Journal of Engineering and Applied Sciences 16 (4):147-151.
    In this study, an automatic heat dispel system for DINGSON Biscuit Oven have been designed and simulated using Proteus program successfully. This system uses thermocouple temperature sensor to sense the oven temperature and automatically open and close the dispel system. The temperature in which the dispel open and close can be adjusted any time the operator needs to adjust it.
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  6.  85
    Adaptive Control Using Nonlinear Autoregressive-Moving Average-L2 Model for Realizing Neural Controller for Unknown Finite Dimensional Nonlinear Discrete Time Dynamical Systems.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - Journal of Engineering and Applied Sciences 16 (3):130-137.
    This study considers the problem of using approximate way for realizing the neural supervisor for nonlinear multivariable systems. The Nonlinear Autoregressive-Moving Average (NARMA) model is an exact transformation of the input-output behavior of finite-dimensional nonlinear discrete time dynamical organization in a hoodlum of the equilibrium state. However, it is not convenient for intention of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate technique are used for realizing the neural supervisor to (...)
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