Integral Sliding Mode Control and Gain-Scheduled Modified Utkin Observer for an Underground Coal Gasification Energy Conversion Process

Ali Arshad Uppal, Saif Siddique Butt, Aamer Iqbal Bhatti, Harald Aschemann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

One of the challenging control problems of an underground coal gasification (UCG) process involves maintaining a desired heating value from the extracted product gases. In this paper, a model-based control and state estimation of UCG process is described. For the purpose of control and state estimation, a sophisticated model of the UCG process using partial differential equations is approximated by a gain-scheduled nonlinear control-oriented model. Based on this approximated plant model, a robust integral sliding mode control is designed to track a desired trajectory of the heating value. Furthermore, for the estimation of unknown states of the system, a gain-scheduled modified Utkin observer is designed as well. The robustness of the nonlinear control and estimation techniques is assessed by introducing parametric uncertainties in the UCG plant. The simulation results highlight the effectiveness of the proposed nonlinear control and estimation techniques in comparison to a conventional PI controller.

Original languageEnglish
Title of host publication2018 23rd International Conference on Methods and Models in Automation and Robotics, MMAR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages357-362
Number of pages6
ISBN (Electronic)9781538643259
DOIs
StatePublished - 8 Oct 2018
Externally publishedYes
Event23rd International Conference on Methods and Models in Automation and Robotics, MMAR 2018 - Miedzyzdroje, Poland
Duration: 27 Aug 201830 Aug 2018

Publication series

Name2018 23rd International Conference on Methods and Models in Automation and Robotics, MMAR 2018

Conference

Conference23rd International Conference on Methods and Models in Automation and Robotics, MMAR 2018
Country/TerritoryPoland
CityMiedzyzdroje
Period27/08/1830/08/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering
  • Control and Optimization

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