Skip to main navigation Skip to search Skip to main content

An expert 2DOF fractional order fuzzy PID controller for nonlinear systems

  • Vijay Mohan*
  • , Himanshu Chhabra
  • , Asha Rani
  • , Vijander Singh
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This work presents a generic two-degree-of-freedom fractional order fuzzy PI-D (2DOF FOFPI-D) controller dedicated to a class of nonlinear systems. The control law for proposed scheme is derived from basic 2DOF fractional order PID controller in discrete domain. Expert intelligence is embedded in overall derived control law by utilizing formula-based fuzzy design methodology. The controller structure comprises of fractional order fuzzy PI (FOFPI) and fractional order derivative filter to handle multiple issues and provides flexibility in design and self-tuning control feature. Further, the proposed scheme is compared with its integer order counterpart and 2DOF PI-D controller for coupled nonlinear 2-link robotic arm in real operating environment. The parameters of designed controllers are optimally tuned using multi-objective non-dominated sorting genetic algorithm-II for attaining low variation in control effort and error index. Intensive simulation studies are performed to analyze trajectory tracking, model uncertainty, disturbance due to cogging, sensor noise and noise as well as disturbance rejection simultaneously. Results demonstrate the superior performance of 2DOF FOFPI-D controller as compared to other designed controllers in the facets of different operating conditions.

    Original languageEnglish
    Pages (from-to)4253-4270
    Number of pages18
    JournalNeural Computing and Applications
    Volume31
    Issue number8
    DOIs
    Publication statusPublished - 01-08-2019

    All Science Journal Classification (ASJC) codes

    • Software
    • Artificial Intelligence

    Fingerprint

    Dive into the research topics of 'An expert 2DOF fractional order fuzzy PID controller for nonlinear systems'. Together they form a unique fingerprint.

    Cite this