Control of PEM fuel cell system via higher order sliding mode control

IF 1.3 Q4 AUTOMATION & CONTROL SYSTEMS International Journal of Automation and Control Pub Date : 2012-01-01 DOI:10.1504/IJAAC.2012.051892
S. Rostami, A. R. Noei, Reza Gaderi
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引用次数: 2

Abstract

This paper presents a multi-input multi-output (MIMO) dynamic model of polymer electrolyte membrane (PEM) fuel cells. A non-linear controller is designed to prolong the stack life of the PEM fuel cell. A moderate deviation between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell. Therefore, a second-order sliding mode strategy is applied to the PEM fuel cell system. This controller is combined with a new step by step differentiators as an output-feedback controller. The differentiator estimates a successive derivative of the measured error signal up to n – 1 order after a finite time transient. Simulation procedure shows performance of the SOSM approach to control PEMFC stack pressure to provide robustness against uncertainties and disturbances.
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PEM燃料电池系统的高阶滑模控制
提出了聚合物电解质膜燃料电池的多输入多输出(MIMO)动力学模型。为了延长PEM燃料电池的堆寿命,设计了非线性控制器。氢氧分压之间的适度偏差会导致燃料电池中的膜严重损坏。因此,将二阶滑模策略应用于PEM燃料电池系统。该控制器与一种新的阶跃微分器相结合作为输出反馈控制器。微分器估计测量误差信号在有限时间暂态后的连续导数,最高可达n - 1阶。仿真结果表明,SOSM方法能够有效地控制PEMFC堆叠压力,对不确定性和干扰具有鲁棒性。
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来源期刊
International Journal of Automation and Control
International Journal of Automation and Control AUTOMATION & CONTROL SYSTEMS-
自引率
41.70%
发文量
50
期刊介绍: IJAAC addresses the evolution and realisation of the theory, algorithms, techniques, schemes and tools for any kind of automation and control platforms including macro, micro and nano scale machineries and systems, with emphasis on implications that state-of-the-art technology choices have on both the feasibility and practicability of the intended applications. This perspective acknowledges the complexity of the automation, instrumentation and process control methods and delineates itself as an interface between the theory and practice existing in parallel over diverse spheres. Topics covered include: -Control theory and practice- Identification and modelling- Mechatronics- Application of soft computing- Real-time issues- Distributed control and remote monitoring- System integration- Fault detection and isolation (FDI)- Virtual instrumentation and control- Fieldbus technology and interfaces- Agriculture, environment, health applications- Industry, military, space applications
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