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Robust control design for air breathing proton exchange membrane fuel cell system via variable gain second‐order sliding mode

机译:可变增益二阶滑模的空气呼吸质子交换膜燃料电池系统的鲁棒控制设计

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摘要

The nonlinear and time‐dependent characteristic and unknown modeling uncertainty of proton exchange membrane fuel cell (PEMFC) such as complex electro‐chemical, thermal, and fluid mechanic phenomena make its controller design quite challenging. In this paper, a controller based on a super twisting algorithm (STA) with variable gains is proposed to control the air breathing system of PEMFC. The strategy includes regulating the oxygen excess ratio ( ) for preventing the stack oxygen starvation and maintaining optimum net power output in spite of external disturbances and model uncertainties. The proposed algorithm has the main advantages of the fixed gain STA, such as robustness against the disturbance and parametric uncertainties with the unknown boundary, chattering reduction, and finite time convergence. The Lyapunov analysis was proposed to assess the stability of the Variable Gain Super Twisting Algorithm (VGSTA). The results verified the effectiveness of the proposed controller with attaining robust regulation against uncertainties, disturbances, and noisy circumstance compared to fixed gain SOSM controllers.
机译:质子交换膜燃料电池(PEMFC)的非线性和随时间变化的特性以及未知的建模不确定性(例如复杂的电化学,热学和流体力学现象)使其控制器设计颇具挑战性。本文提出了一种基于可变增益的超扭曲算法(STA)的控制器来控制PEMFC的呼吸系统。该策略包括调节氧气过量比(),以防止烟囱氧气不足,并在外部干扰和模型不确定性的情况下保持最佳的净功率输出。所提出的算法具有固定增益STA的主要优点,例如对干扰的鲁棒性和未知边界下的参数不确定性,抖动减少和有限时间收敛。提出了Lyapunov分析,以评估可变增益超扭曲算法(VGSTA)的稳定性。结果证明,与固定增益SOSM控制器相比,该控制器具有针对不确定性,干扰和嘈杂环境进行鲁棒调节的有效性。

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