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  1. 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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  2. 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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  3. 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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  4. Comparison of a Nonlinear Magnetic Levitation Train Parameters using Mixed H 2/H infinity and Model Reference Controllers.Mustefa Jibril, Mesay Tadesse & Nurye Hassen - 2021 - ACE Journal of Computer Science and Engineering 1 (2):17-22.
    To improve the riding performance and levitation stability of a high‐speed magnetic levitation (maglev) train, a control strategy based on mixed H 2/H4 with regional pole placement and model‐reference controllers are proposed. First, the nonlinear maglev train model is established, then the proposed system is designed to observe the movement of a suspension frame and a control strategy based on mixed H 2/H4 with regional pole placement and model‐reference control method are proposed. Test and analysis of the proposed system has (...)
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  5. Position Control of a Three Degree of Freedom Gyroscope using Optimal Control.Mustefa Jibril, Messay Tadese & Nurye Hassen - 2020 - New York Science Journal 13 (11):1-5.
    In this paper, a 3 DOF gyrscope position control have been designed and controlled using optimal control theory. An input torque has been given to the first axis and the angular position of the second axis have been analyzed while the third axis are kept free from rotation. The system mathematical model is controllable and observable. Linear Quadratic Integral (LQI) and Linear Quadratic State Feedback Regulator (LQRY) controllers have been used to improve the performance of the system. Comparison of the (...)
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  6. 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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  7. Modeling and Performance Analysis of Shell Tube Surface Condenser under Lumped Parameters using Fuzzy Self-tuning PI Controller.Mustefa Jibril, Mesay Tadesse, Nurye Hassen & Yonas Abebe - 2020 - International Journal of Electronics and Electrical Engineering Systems 3 (4):1-8.
    Shell tube surface condenser (STSC) is a heat exchanger system that exchange a high pressure steam into low pressure water and it is widely used in applications like textile industries and nuclear power plants. The modelling of the system has been established based on lumped parameters. In this paper, a fuzzy expert system is developed in order to improve the performance of the condenser. A pressure feedback system has been developed to analyze the effect of the condenser output temperature, circulating (...)
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