In this study, an observer for estimating the state and unknown inputs is proposed for monitoring anaerobic digestion processes. This estimator is based on a dynamic model considering acidogenesis and methanogenesis, and consists of three sub-observers: (a) a gramian-based fixed-time convergent observer for the inlet chemical oxygen demand (COD) and the acidogenic bacteria population, (b) an asymptotic observer for the methanogenic bacteria population, and (c) a super-twisting observer for systems with time-varying parameters to estimate the inlet volatile fatty acid (VFA) concentration. These sub-observers can be designed independently, which greatly simplifies the tuning process. Proofs of convergence are developed and simulation tests show the performance of the estimation scheme as compared to classical extended Kalman filtering.

在这项研究中，提出了一种用于估计状态和未知输入的观察器来监测厌氧消化过程。该估计器基于考虑酸生成和产甲烷作用的动态模型，由三个子观测器组成：(a) 入口化学需氧量 (COD) 和产酸细菌种群的基于格拉姆的固定时间收敛观测器，(b ) 对产甲烷细菌种群的渐近观测器，和 (c) 用于具有时变参数的系统的超扭曲观测器，以估计入口挥发性脂肪酸 (VFA) 浓度。这些子观察者可以独立设计，大大简化了调优过程。开发了收敛证明，仿真测试显示了估计方案与经典扩展卡尔曼滤波相比的性能。