Model Predictive Control Based on System Re-Identification (MPC-SRI) to Control Bio-H2 Production from Biomass

Abdul Wahid, H. M.H. Taqwallah

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Compressors and a steam reformer are the important units in biohydrogen from biomass plant. The compressors are useful for achieving high-pressure operating conditions while the steam reformer is the main process to produce H2 gas. To control them, in this research used a model predictive control (MPC) expected to have better controller performance than conventional controllers. Because of the explicit model empowerment in MPC, obtaining a better model is the main objective before employing MPC. The common way to get the empirical model is through the identification system, so that obtained a first-order plus dead-time (FOPDT) model. This study has already improved that way since used the system re-identification (SRI) based on closed loop mode. Based on this method the results of the compressor pressure control and temperature control of steam reformer were that MPC based on system re-identification (MPC-SRI) has better performance than MPC without system re-identification (MPCWSRI) and the proportional-integral (PI) controller, by % improvement of 73% against MPCWSRI and 75% against the PI controller.

Original languageEnglish
Article number012061
JournalIOP Conference Series: Materials Science and Engineering
Volume316
Issue number1
DOIs
Publication statusPublished - 28 Mar 2018
Event15th International Conference on Quality in Research, QiR 2017 - Nusa Dua, Bali, Indonesia
Duration: 24 Jul 201727 Jul 2017

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