List of Articles siamak azargoshasb

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  1 - Design Discrete Robust Adaptive Fuzzy Control for Asymptotic Tracking of Articulated Robot Manipulator
  moslem zarei siamak azargoshasb najmeh cheraghi shirazi
  20.1001.1.29809231.1400.10.40.4.8
  Robot manipulators are nonlinear multivariable systems with high couplings and various uncertainties. Although, adaptive and robust control methods are suggested to overcome the uncertainties including parametric uncertainty, un-modeled dynamics, external disturbances a More

  Robot manipulators are nonlinear multivariable systems with high couplings and various uncertainties. Although, adaptive and robust control methods are suggested to overcome the uncertainties including parametric uncertainty, un-modeled dynamics, external disturbances and discretization error, they face many challenges because of the complexity in robot dynamics. A fuzzy system can be used as a universal approximator for any nonlinear system. This feature has been efficiently used to design the adaptive fuzzy controllers. Adaptive fuzzy control systems are designed based on guaranteeing stability. Since practical implementation of the control law is carried out using digital processors, designing a discrete-time adaptive fuzzy controller for robot manipulators based on the voltage control strategy and proposed control systems stability analysis is suggested in this paper. In this paper, a new method is developed for compensating the approximation error of the fuzzy system which does not needed integration of tracking error. Moreover, the proposed discrete-time adaptive fuzzy with position feedback control law requires feedbacks of joint positions only. On the other hand, the fuzzy system approximation error and the discretization error are well compensated for asymptotic tracking of the desired path. The proposed robust Adaptive Fuzzy control law is simulated on an articulated robot. The simulation results show that the tracking error is negligible and the value of the second joint tracking error with the highest error at the end point of the simulation time is about radians. The parameters are well matched and the motors behave well under the maximum allowable voltage. Manuscript profile
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  2 - Model-Free Discrete Time Control for Scara Robot Manipulators Using Descending Gradient Algorithm
  reza zarin siamak azargoshasb
  20.1001.1.29809231.1400.11.41.5.4
  Discrete control of the robot manipulators with uncertain model is the purpose of this paper. The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimation of uncertainty as unknown function. An adaptive mechanis More

  Discrete control of the robot manipulators with uncertain model is the purpose of this paper. The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimation of uncertainty as unknown function. An adaptive mechanism is proposed in order to overcome uncertainties. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a novel gradient descent algorithm. The proposed model-free discrete control is robust against all uncertainties associated with the robot manipulator and actuators including model’s uncertainty and external disturbances. The most gradient descent algorithms have used a known cost function based on the tracking error for adaptation whereas the proposed algorithm has proposed a cost function based on the uncertainty estimation error. Then, the uncertainty estimation error is calculated from the joint position error and its derivative using the closed-loop system. Most control algorithms require all state variable feedback to ensuring stability for the robot manipulators. Practical implementation of this control method is easy because it has a decentralized structure and measures only from the joint position. The simulation results confirm the correct operation of this method and we will prove the stability of the control system. Manuscript profile
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  3 - Robust Sliding Mode Control of Robot Manipulators Using the Fourier Series Expansion in the Presence of Uncertainty
  Abdullah Hadipoor Siamak Azargoshasb Abdolrasool Ghasemi
  10.30495/jce.2022.693456
  20.1001.1.29809231.1401.12.46.6.2
  In this paper, a robust dynamic slip mode controller for an electrical robot manipulator is presented. The control law calculates the motor voltage based on the voltage control strategy. Uncertainties are estimated using the Fourier series expansion and the cutting erro More

  In this paper, a robust dynamic slip mode controller for an electrical robot manipulator is presented. The control law calculates the motor voltage based on the voltage control strategy. Uncertainties are estimated using the Fourier series expansion and the cutting error is compensated. Fourier coefficients are adjusted based on stability analysis. Also in this paper is the design of a robust controller using a new adaptive Fourier series extension. Compared to previous related works based on the Fourier series expansion, the advantage of this paper is that it provides a matching law for the main frequency of the Fourier series expansion and thus eliminates the need for trial and error in its regulation. A case study of a Scara robot powered by DC magnet electric motors. The effect of uncertainty estimation based on the Fourier series expansion is studied instead of using the sign function. The proposed method is also compared with Legendre polynomials. The simulation results confirm the robust and satisfactory performance of the proposed controller. Manuscript profile
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  4 - Robust Control of Robot Manipulators using Particle Swarm Optimization Method
  Fazlollah Rajaee Seyed Mohammad-Ali Riazi Siamak Azargoshasb
  10.30495/jce.2022.691482
  20.1001.1.29809231.1401.12.45.6.0
  In this paper, a new method for robust control is used. The whole robotic system, including the robot arm and motors in control, is considered. The main purpose of this article is to obtain the best results of the control law in order to achieve the minimum tracking err More

  In this paper, a new method for robust control is used. The whole robotic system, including the robot arm and motors in control, is considered. The main purpose of this article is to obtain the best results of the control law in order to achieve the minimum tracking error, which uses congestion optimization. Also, the designers of the control law are based on the nominal model . The real model uses intelligent systems. Control to resistance is evaluated by analysis and analysis.The stability of the system is demonstrated using Lyapunov's direct method, and the simulation results show the effectiveness of the proposed methods applied to a spherical robot driven by permanent magnet dc motors. Using the simulation results, the optimal values ​​of the parameters in the torque controllers have not converged to their true values ​​due to the large modelless dynamics, while they have converged to their true values ​​in the voltage control because it has only parametric uncertainty. . Also, the torque control law requires position vector, velocity vector and acceleration vector feedback.These feedback can not be easily obtained. In contrast, the law of voltage control requires feedback from the position vector, velocity vector, current vector, and time derivative. These feedback can be easily accessed. Manuscript profile