Researcher:
Ulasyar, Abasin

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Abasin

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Ulasyar

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Ulasyar, Abasin

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2016 - 2019102020 - 20222

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Now showing 1 - 10 of 12
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    Optimal output voltage control of solar photovoltaic power system
    (Ieee, 2018) Zohaib, Adil; N/A; N/A; Ulasyar, Abasin; Zad, Haris Sheh; Researcher; PhD Student; Manufacturing and Automation Research Center (MARC); N/A; Graduate School of Sciences and Engineering; N/A; N/A
    The intensity of the sunlight varies throughout the day due to various environmental factors. This variation in the intensity of the incoming sunlight falling on the solar photovoltaic (PV) system makes the overall output voltage of the system unstable. The sunlight variation causes the generated output voltage to change abruptly. Therefore, for regulating the output voltage, a buck-boost converter should be used, which will accordingly buck or boost the output voltage based on the sunlight intensity variations. In this article, an optimal model predictive controller (MPC) is designed and analyzed for regulating the output of the overall PV system. The designed MPC controller optimally controls the PWM duty cycle in order to stabilize and adjust the overall voltage of the PV system. The response of the designed optimal controller is also compared with the classical control techniques as well. The results show that the designed MPC controller regulates the output response of the PV system very well in the presence of system parameters Variations and uncertainties.
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    Optimal controller design for self-balancing two-wheeled robot system
    (Institute of Electrical and Electronics Engineers (IEEE), 2017) Zohaib, Adil; Hussain, Syed Shahzad; N/A; N/A; Zad, Haris Sheh; Ulasyar, Abasin; PhD Student; Researcher; N/A; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; N/A; N/A; N/A
    In this paper an optimal controller is designed for a self-balancing two-wheeled robot system based on the robust Model Predictive Control (MPC) scheme. The MPC controller computes the trajectory of the manipulated variable in order to optimize the behavior of the system future output. A limited time window is used for the optimization described by the length of time and initial time. By minimizing the cost function, the optimal control is found within the moving window. The proposed controller is simulated using Matlab/Simulink. Performance of the optimal controller based on MPC scheme is compared with that of a PID controller. The simulation results show better stability and improved reference position tracking for the MPC based optimal controller with good robustness against the perturbations in the system model.
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    Robust Model Predictive position Control of direct drive electro-hydraulic servo system
    (Institute of Electrical and Electronics Engineers (IEEE), 2016) Zohaib, Adil; N/A; N/A; Zad, Haris Sheh; Ulasyar, Abasin; PhD Student; Researcher; N/A; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; N/A; N/A; N/A
    In this paper a robust Model Predictive Controller (MPC) is designed for direct drive electro-hydraulic position servo system in presence of unknown dynamics and uncertain nonlinearities. While considering the nonlinearity of dead zone and also the saturation in direct drive electro-hydraulic servo system, the PID controller suffers from problem of poor robustness and also adaptability. In MPC control technique, model of the position servo system is used in order to predict the future evaluation of the plant for optimizing the control signal. The proposed controller is tested for different scenarios of unmeasured and measured disturbances to the system. The results presented show enhancement in the position tracking performance with the rejection of both measured disturbances and unmeasured Gaussian disturbances. The performance of MPC is also compared with PID controller. The control accuracy, robustness capability and response speed of the position servo system have been significantly improved with MPC controller.
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    Adaptive control of self-balancing two-wheeled robot system based on online model estimation
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) N/A; N/A; Zad, Haris Sheh; Ulasyar, Abasin; PhD Student; Researcher; N/A; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; N/A; N/A; N/A
    In this article, an adaptive model predictive controller (MPC) is designed for the position control of the self-balancing two-wheeled robot system. The system future output is optimized using the MPC controller by computing the manipulated variable trajectory. Traditional MPC uses a Linear-Time-Invariant (LTI) dynamic model of the system for the prediction of future behavior. The model of the self-balancing two-wheeled robot system is strongly nonlinear which degrades the prediction accuracy of the traditional MPC controller. Therefore, an adaptive MPC controller is designed based on linear-time-varying Kalman filter which online tunes and updates the estimated system parameters and accordingly produces the control effort in the presence of the input/output and state constraints. The performance of the proposed controller is compared with the traditional MPC controller and PID controller. The results show improved reference tracking and better stability for the proposed adaptive MPC controller as compared to traditional MPC and PID controller.
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    Design and analysis of a new magneto rheological damper for washing machine
    (Korean Soc Mechanical Engineers, 2018) N/A; Department of Mechanical Engineering; Ulasyar, Abasin; Lazoğlu, İsmail; Researcher; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); N/A; College of Engineering; N/A; 179391
    In this article, a new magneto rheological (MR) sponge damper is proposed for suppression of vibrations in a washing machine. The article presents design optimization of geometric parameters of MR sponge damper (MRSD) using the finite element analysis (FEA) and first order derivative techniques for a washing machine. The article explains the hysteresis behavior and the relationship of damping force with input current for the proposed MRSD. Moreover, the characteristics of the MRSD such as energy dissipation and equivalent damping coefficient are investigated experimentally in terms of input current and excitation amplitude. The passive dampers installed in washing machine are ineffective in reducing unwanted vibrations at resonant frequencies due to real time unbalanced mass. For this purpose, a test setup is established in order to compare the performance of passive dampers with the proposed MRSDs in a washing machine. It is noticed that MRSDs reduce average vibrations of 75.61 % in a low frequency band, whereas in a high frequency band, the MRSDs lessen average vibrations of 30.57 % in a washing machine. In order to determine the performance of proposed design MRSD, a detailed comparison of the performance parameters, such as total damping force, passive force, maximum average vibrations after suppression by MR dampers, maximum current and power ratings is provided with the existing designs of MR damper for washing machine from the literature.
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    Active damping of chatter in the boring process via variable gain sliding mode control of a magnetorheological damper
    (Elsevier, 2021) N/A; N/A; Department of Mechanical Engineering; Saleh, Mostafa Khalil Abdou; Ulasyar, Abasin; Lazoğlu, İsmail; PhD Student; Researcher; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; N/A; College of Engineering; N/A; N/A; 179391
    In this article, a sliding mode control of a magnetorheological fluid damper is presented for active damping of chatter in the boring process for the first time. A boring bar is integrated with an in-house developed magnetorheological fluid damper system. The variable gain super twisting sliding mode control algorithm is designed and implemented for suppressing the chatter in the boring process. Simulations of the controller show its fast response and robustness against disturbances and parametric uncertainties. Validation cutting tests performed under various machining conditions showed that the stability limit can be increased significantly with the sliding mode control of the magnetorheological fluid damper.
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    Robust sliding mode voltage control of three-phase power system converter
    (Ieee, 2018) Zohaib, Adil; N/A; N/A; Zad, Haris Sheh; Ulasyar, Abasin; PhD Student; Researcher; N/A; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; N/A; N/A; N/A
    For the three phase converters, the conventional linear controllers do not provide an efficient and robust control objective because of the uncertainties, nonlinearities, system perturbations and unmodeled dynamics present in the system model. In this article, a sliding mode controller (SMC) is being designed and analyzed for a three-phase converter. The overall control loop is designed in to two separate loops, the outer loop containing control of voltage and the inner loop containing the control of current. In the given controller scheme, the shaping of the supply currents and the regulation of the voltage are obtained simultaneuosly, thus providing a robust response. The proposed controller is analyzed using Matlab/Simulink. The proposed controller consists of two separate parts, the switching part which forces the trajectory to sliding surface, and also the continuous part for the system to be remained on the sliding surface. The designed controller comparison is also done with the classical control technique. The results show good robustness and better stability of the overall system over a larger operation range with the designed SMC controller.
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    Robust & optimal model predictive controller design for twin rotor MIMO system
    (Institute of Electrical and Electronics Engineers (IEEE), 2016) N/A; N/A; Ulasyar, Abasin; Zad, Haris Sheh; Researcher; PhD Student; Manufacturing and Automation Research Center (MARC); N/A; Graduate School of Sciences and Engineering; N/A; N/A
    In this paper a two degree of freedom Twin Rotor MIMO System (TRMS), which is employed to model the pitch and yaw directions of a helicopter, is considered. Using the model of TRMS, MATLAB simulaitons are performed. The open loop model of the system is unstable. Since the system is both controllable and observable, a robust and optimal Model Predictive Controller (MPC) is designed to control the system. The simulations of the controller give better results as compared to the one obtained from LQR approach.
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    Robust speed controller design for the variable-speed wind turbine power system
    (Ieee, 2018) Zad, Haris Sheh; Zohaib, Adil; N/A; Ulasyar, Abasin; Researcher; Manufacturing and Automation Research Center (MARC); N/A; N/A
    The use of an appropriate control scheme can greatly boost the performance of the wind energy systems. The wind power systems that are connected to the grid side contain highly nonlinear characteristics and therefore, demand robust control scheme for their proper operation. The classical control schemes do not provide robustness against the nonlinearities and uncertainties present in the system. In this article, a robust sliding mode controller (SMC) is being designed and analyzed for regulating the speed of the wind turbine system in the existence of unmodeled dynamics, external perturbations and system uncertainties. The controller stability is given using the theory of Lyapunov stability. The designed controller performance is also compared to classical control techniques. The designed controller shows a better system response with the elimination of the steady state error and good robustness against system uncertainties.
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    Adaptive radial basis function neural network based tracking control of Van der Pol oscillator
    (Institute of Electrical and Electronics Engineers (IEEE), 2017) Zohaib, Adil; Hussain, Syed Shahzad; N/A; N/A; Ulasyar, Abasin; Zad, Haris Sheh; Researcher; PhD Student; Manufacturing and Automation Research Center (MARC); N/A; Graduate School of Sciences and Engineering; N/A; N/A
    In this paper an online adaptive Radial Basis Function (RBF) controller is designed and simulated for the tracking control of Van der Pol oscillator. Van der pol oscillator is a nonlinear oscillator which is used for the modeling of various laser, mechanical and electrical oscillatory systems. The control and adaptive laws for the RBF controller are designed based on the neural network approximation. Lyapunov stability criterion is used in order to analyze the stability of the designed control and adaptive laws. Matlab/Simulink tool is used for the simulation of the designed adaptive controller for the tracking control of Van der Pol oscillator. The designed controller performance is tested with the uncertain system parameters and in the presence of disturbance in the system. The results of simulation show better reference tracking of the oscillator with the designed adaptive controller having good set speed and control accuracy. The designed controller has good robustness against the system perturbations and disturbances.