Rapid load following of an SOFC power system via stable fuzzy predictive tracking controller

Tiejun Zhang; Gang Feng

doi:10.1109/TFUZZ.2008.2011135

Rapid load following of an SOFC power system via stable fuzzy predictive tracking controller

Tiejun Zhang, Gang Feng

Mechanical & Nuclear Engineering

City University of Hong Kong

Research output: Contribution to journal › Article › peer-review

56 Scopus citations

Abstract

The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.

Original language	British English
Pages (from-to)	357-371
Number of pages	15
Journal	IEEE Transactions on Fuzzy Systems
Volume	17
Issue number	2
DOIs	https://doi.org/10.1109/TFUZZ.2008.2011135
State	Published - 2009

Keywords

Fuel cell
Fuzzy systems
Identification
Input-to-state stability
Load following
Output tracking
Predictive control

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TFUZZ.2008.2011135

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title = "Rapid load following of an SOFC power system via stable fuzzy predictive tracking controller",

abstract = "The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.",

keywords = "Fuel cell, Fuzzy systems, Identification, Input-to-state stability, Load following, Output tracking, Predictive control",

author = "Tiejun Zhang and Gang Feng",

note = "Funding Information: Dr. Zhang was the recipient of the Outstanding M.Sc. Dissertation Award of Jiangsu Province of China. Funding Information: Manuscript received December 22, 2007; revised June 19, 2008 and September 9, 2008. First published December 22, 2008; current version published April 1, 2009. This work was supported in part by the Hong Kong Research Grant Council under CityU 112806 and by the National Natural Science Foundation of China under Grant 50640460116.",

year = "2009",

doi = "10.1109/TFUZZ.2008.2011135",

language = "British English",

volume = "17",

pages = "357--371",

journal = "IEEE Transactions on Fuzzy Systems",

issn = "1063-6706",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Rapid load following of an SOFC power system via stable fuzzy predictive tracking controller

AU - Zhang, Tiejun

AU - Feng, Gang

N1 - Funding Information: Dr. Zhang was the recipient of the Outstanding M.Sc. Dissertation Award of Jiangsu Province of China. Funding Information: Manuscript received December 22, 2007; revised June 19, 2008 and September 9, 2008. First published December 22, 2008; current version published April 1, 2009. This work was supported in part by the Hong Kong Research Grant Council under CityU 112806 and by the National Natural Science Foundation of China under Grant 50640460116.

PY - 2009

Y1 - 2009

N2 - The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.

AB - The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.

KW - Fuel cell

KW - Fuzzy systems

KW - Identification

KW - Input-to-state stability

KW - Load following

KW - Output tracking

KW - Predictive control

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U2 - 10.1109/TFUZZ.2008.2011135

DO - 10.1109/TFUZZ.2008.2011135

M3 - Article

AN - SCOPUS:67349121266

SN - 1063-6706

VL - 17

SP - 357

EP - 371

JO - IEEE Transactions on Fuzzy Systems

JF - IEEE Transactions on Fuzzy Systems

IS - 2

ER -

Rapid load following of an SOFC power system via stable fuzzy predictive tracking controller

Abstract

Keywords

UN SDGs

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