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Articles by Iraj Hassanzadeh
Total Records ( 4 ) for Iraj Hassanzadeh
  Iraj Hassanzadeh , Abbas Harifi and Farid Arvani
  This research investigates the performance of an adaptive controller for five-bar linkage robot. The proposed controller was entirely independent on the physical specifications of the robot. The controller was examined as the dynamics of the mechanical system varies for various environment conditions, which make it an ambiguous system. In this study, the introduced controller was designed based on the governing ideal Euler-Lagrange equations on the robot but assessed using the on-line dynamic simulation of the mechanism for different target configurations which guarantees the high performance and effectiveness of the designed controller.
  Iraj Hassanzadeh , Saleh Mobayen and Abbas Harifi
  The Rotary Inverted Pendulum (RIP) system is a significant classical problem of control engineering which has been investigated in the past decades. This study presents an optimum Input-Output Feedback Linearization (IOFL) cascade controller utilized Genetic Algorithm (GA). Due to the non-minimum phase behavior of the system, IOFL controller leads to unstable internal dynamics. Therefore a cascade structure is proposed consisting IOFL controller for inner loop with PD controller forming the outer loop. The primary design goal is to balance the pendulum in an inverted position. The control criterion is to minimize the Integral Absolute Error (IAE) of system angles. By minimizing the objective function related to IAE using Binary Genetic Algorithm (BGA), the optimal controller parameters can be assigned. The results verified capability and competent characteristics of the proposed controller. The method can be considered as a promising way for control of various similar nonlinear and under-actuated systems.
  Iraj Hassanzadeh and Saleh Mobayen
  This research presents an optimum approach for designing Rotary Inverted Pendulum (RIP) controller using PSO algorithm. The primary design goal is to balance the pendulum in an inverted position and the control criterion is to minimize the integral absolute error of system angles. Simulation results demonstrate the robustness and effectiveness of proposed controller with regard to parameter variations, various reference trajectory and load disturbances. The proposed method can be considered as a promising way for control of various similar nonlinear systems.
  Iraj Hassanzadeh and Mehdi Abedinpour Fallah
  In this study, we present the local reconstruction of differential-drive mobile robots position and orientation with an accurate odometry calibration. Starting from the encoders readings and assuming an absolute measurement available, Augmented Extended and Unscented Kalman Filters (AEUKF) are proposed to localize the vehicle while estimating a proper set of odometric parameters. In order to compare their estimation performances explicitly, both observers are designed for the same mobile robot model and run with the equal covariance matrices under the identical initial conditions. In the simulation results, it is shown that Augmented Unscented Kalman Filter (AUKF) outperforms the Augmented Extended Kalman Filter (AEKF).
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