Researcher:
Zad, Haris Sheh

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PhD Student

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Haris Sheh

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Zad

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Zad, Haris Sheh

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2016 - 20189

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Researcher Of Publications: search.filters.isAuthorOfPublication.a08b6ad5-baa8-4242-a71f-5d0ed17a8cc9

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Now showing 1 - 9 of 9
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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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    Design and adaptive sliding-mode control of hybrid magnetic bearings
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) N/A; N/A; Department of Mechanical Engineering; Zad, Haris Sheh; Khan, Talha Irfan; Lazoğlu, İsmail; PhD Student; PhD Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 179391
    In this paper, a hybrid magnetic bearing (HMB) prototype system is designed and analyzed. Two compact bearings are used to suspend the rotor in five degrees of freedom. Electromagnets are used for axial suspension of the rotor, while permanent magnets are used for the passive radial stability. A brushless DC motor is designed in order to rotate the shaft around its axis. The 3-D finite-element model of the HMB system is established and distribution of magnetic fields in the air gaps and magnetic forces on the rotor under various control currents and displacements is calculated. A nonlinear adaptive sliding-mode controller is designed for the position control of the rotor in axial direction. Since the control characteristics of the active magnetic bearing system are highly nonlinear and time varying with external interference, a radial basis function compensator is designed first, and then, a sliding-mode control law is used to generate the control input. The stability analysis for the designed controller is given based on the Lyapunov theorem. Experimental setup is built to guide the design process. The performance of the HMB system based on the designed control algorithm is evaluated under different operating conditions.
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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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    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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    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.
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    Development of a novel shrouded impeller pediatric blood pump
    (Springer Japan Kk, 2018) N/A; N/A; N/A; Department of Mechanical Engineering; N/A; Khan, Talha Irfan; Zad, Haris Sheh; Lazoğlu, İsmail; Yalçın, Özlem; PhD Student; PhD Student; Faculty Member; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; N/A; 179391; 218440
    The aim of this work was to analyze a shrouded impeller pediatric ventricular assist device (SIP-VAD). This device has distinctive design characteristics and parameter optimizations for minimization of recirculation flow and reduction in high-stress regions that cause blood damage. Computational Fluid Dynamics (CFD) simulations were performed to analyze the optimized design. The bench-top prototype of SIP-VAD was manufactured with biocompatible stainless steel. A study on the hydrodynamic and hemodynamic performance of the SIP-VAD was conducted with predictions from CFD and actual experimentation values, and these results were compared. The CFD analysis yielded a pressure range of 29-90 mmHg corresponding to flow rates of 0.5-3 L/min over 9000-11000 rpm. The predicted value of the normalized index of hemolysis (NIH) was 0.0048 g/100 L. The experimental results with the bench-top prototype showed a pressure rise of 30-105 mmHg for the flow speed of 8000-12000 rpm and flow rate of 0.5-3.5 L/min. The maximum difference between CFD and experimental results was 4 mmHg pressure. In addition, the blood test showed the average NIH level of 0.00674 g/100 L. The results show the feasibility of shrouded impeller design of axial-flow pump for manufacturing the prototype for further animal trials.