Repository logo
Communities & Collections
All of DSpace
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Criollo Gordillo, Michael Alexander"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Publication
    An explorative study of search algorithms applied to the gain scheduling in PID controllers
    (IEEE, 2023) Minchala Ávila, Luis Ismael; Criollo Gordillo, Michael Alexander
    The efficiency of a proportional-integral-derivative (PID) controller depends directly on the values of the gains Kp, Ki, and Kd. In this context, changes in the process dynamics imply degradation in the performance of the closed-loop control system. Several artificial intelligence techniques are used to adjust the PID parameters to improve the control system’s performance. However, there is little exploratory evidence about how primitive techniques with low computational costs can contribute to solve this gain calculation task. This paper explores and compares three algorithms applied to the real-time gain calculation of PID controllers: fuzzy logic (FGS-PID), simulated annealing (SA-PID), and the A⋆search method (A⋆PID). The validation of the operation of these schemes is carried out through simulations as well as by applying these controllers to a two-tank liquid-level control system. Experimental results show the algorithms’ effectiveness to improve the control system’s global performance and to add passive fault-tolerance capabilities.
  • Loading...
    Thumbnail Image
    Item
    Diseño e implementación de un controlador PID de ganancia programada usando técnicas de inteligencia artificial
    (Universidad de Cuenca, 2023-03-07) Criollo Gordillo, Michael Alexander; Minchala Ávila, Luis Ismael
    This paper analyzes three new control strategies that improve system response and its com- parison with classic PID control. The efficiency of the PID controller depends only on its gains Kp, Ki and Kd. Therefore, the strategies improve the control process by finding the optimal gains through the programed algorithm. The programmed gain control algorithms are based on artificial intelligence techniques such as fuzzy logic, the simulated annealing algorithm and the A* search method, resulting in the FGS-PID, SA-PID and A*-PID controllers. The control algorithms are tested in MATLAB and adapted on the STM32 core-144 embedded system, with the objective of controlling the water level of a multitank system. For this purpose, different performance tests are carried out in simulations and on the real system where the response of the plant to reference changes is evaluated. In addition, the settling time and percentage of overshoot are used as performance indexes. Also, the operation of the control system is tested by introducing possible failures in the plant, such as through leaks in the tanks caused by a hole in the bottom. Finally, the results show the effectiveness of the algorithms in reducing the settling time and overshoot in the response of the multitank system, furthermore, adding some tolerance to failures in the system. The aforementioned results allow the tracking of the reference in the presence of faults, which is not achieved with the classical PID control system.

DSpace software copyright © 2002-2026 LYRASIS

  • Privacy policy
  • End User Agreement
  • Send Feedback