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Uniform step-by-step observer for aerobic bioreactor based on super-twisting algorithm

机译:基于超扭曲算法的好氧生物反应器统一步骤观察器

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This paper describes a fixed-time convergent step-by-step high order sliding mode observer for a certain type of aerobic bioreactor system. The observer was developed using a hierarchical structure based on a modified super-twisting algorithm. The modification included nonlinear gains of the output error that were used to prove uniform convergence of the estimation error. An energetic function similar to a Lyapunov one was used for proving the convergence between the observer and the bioreactor variables. A nonsmooth analysis was proposed to prove the fixed-time convergence of the observer states to the bioreactor variables. The observer was tested to solve the state estimation problem of an aerobic bioreactor described by the time evolution of biomass, substrate and dissolved oxygen. This last variable was used as the output information because it is feasible to measure it online by regular sensors. Numerical simulations showed the superior behavior of this observer compared to the one having linear output error injection terms (high-gain type) and one having an output injection obtaining first-order sliding mode structure. A set of numerical simulations was developed to demonstrate how the proposed observer served to estimate real information obtained from a real aerobic process with substrate inhibition.
机译:本文描述了一种特定类型的好氧生物反应器系统的固定时间收敛的逐步高阶滑模观测器。观察者是使用基于改进的超扭曲算法的分层结构开发的。修改包括输出误差的非线性增益,这些非线性增益用于证明估计误差的均匀收敛。一种类似于李雅普诺夫函数的能量函数被用来证明观察者和生物反应器变量之间的收敛。提出了非平稳分析来证明观察者状态到生物反应器变量的固定时间收敛性。测试观察者以解决好氧生物反应器的状态估计问题,该问题由生物量,底物和溶解氧的时间演变来描述。最后一个变量用作输出信息,因为通过常规传感器在线测量它是可行的。数值模拟表明,与具有线性输出误差注入项(高增益类型)和具有输出注入获得一阶滑模结构的观测器相比,该观测器具有优越的性能。已开发了一组数值模拟,以演示拟议的观察者如何估算具有底物抑制作用的真实需氧过程获得的真实信息。

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