• Title of article

    PID Tuning Method on AGV (Automated Guided Vehicle) Industrial Robot

  • Author/Authors

    Jahangir Moshayedi, Ata School of Information Engineering - Jiangxi University of Science and Technology - No 86 - Hongqi Ave - Ganzhou, Jiangxi,341000, China , Shuvam Roy, Atanu School of Information Engineering - Jiangxi University of Science and Technology - No 86 - Hongqi Ave - Ganzhou, Jiangxi,341000, China , Liao, Liefa School of Information Engineering - Jiangxi University of Science and Technology - No 86 - Hongqi Ave - Ganzhou, Jiangxi,341000, China

  • Pages
    14
  • From page
    53
  • To page
    66
  • Abstract
    Controlling a system can be done in various ways and methods. The classical method which even now a day as a solution works is PID which in that with some method three-parameter of controller called P (Proportional), I (Integral), D (Derivational) tuned to have the best controlling response from a system. The AGV robot as the abbreviation of the Automated Guided Vehicle is as a famous robot platform which used in various industries relies on PID controllers in various ways. Each AGV or Machine has its own set of function, hence, in order to accomplish the exact set of workload more efficiently one need to actually tune the PID parameters accordingly so that there cannot be an intolerable amount of energy loss, inefficiency rate, lag, lack of robustness etc. In this paper over than introduction of PID controller and see the effect of each parameter on the real system the compassion between hired methods on AGV robot are investigated. As this review indicates that various PID tune method are used based on system requirements with the help of Lyapunov Direct Method, traditional Ziegler Nichols, Fuzzy controller, human immune system called the humoral, neural network, etc to control the speed and steering of an AGV systems.
  • Keywords
    PID , AGV , PID Tune , Ziegler-Nichols , Automated Guided Vehicle
  • Journal title
    Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering
  • Serial Year
    2019
  • Record number

    2573682