Input concentration estimation for an anaerobic digestion process using EKF and SM observers. A comparative study

被引:0
|
作者
Barbu, Marian [1 ]
Ifrim, George [1 ]
Ceanga, Emil [1 ]
Caraman, Sergiu [1 ]
Petre, Emil [2 ]
Selisteanu, Dan [2 ]
机构
[1] Univ Galatzi, Dept Automat & Elect Engn, Galati, Romania
[2] Univ Craiova, Dept Automat Control, Craiova, Romania
来源
2016 20TH INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC) | 2016年
关键词
Extended Kalman Filter; Sliding Mode Observer; Anaerobic Digestion Process; MECHANICAL SYSTEMS; IDENTIFICATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is well known that in the case of the wastewater treatment bioprocesses, including anaerobic digestion process, usually, the complete knowledge of inputs is not available and therefore the implementation of the control laws becomes a difficult problem. Therefore, in the sequel, for the above mentioned process two observer structures, able to estimate the unknown concentration of the input will be presented and analyzed. The paper deals with a comparative analysis of two types of observers: a stochastic one - Extended Kalman Filter and a deterministic one - Sliding Mode Observer. The estimation methods are analyzed in realistic frame taking into consideration the presence of the measurement noise but especially the usual variations in the case of an anaerobic digestion process, such as the variation of the maximum growth rate of the microorganisms. The effectiveness of the proposed observers has been validated by numerical simulations.
引用
收藏
页码:186 / 191
页数:6
相关论文
共 25 条
  • [21] A comparative study of total dissolved solids in water estimation models using Gaussian process regression with different kernel functions
    Zare Farjoudi, Sahar
    Alizadeh, Zahra
    ENVIRONMENTAL EARTH SCIENCES, 2021, 80 (17)
  • [22] A comparative study of total dissolved solids in water estimation models using Gaussian process regression with different kernel functions
    Sahar Zare Farjoudi
    Zahra Alizadeh
    Environmental Earth Sciences, 2021, 80
  • [23] A COMPARATIVE STUDY OF USING ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM (ANFIS), GAUSSIAN PROCESS REGRESSION (GPR), AND SMRGT MODELS IN FLOW COEFFICIENT ESTIMATION
    Mehdi, Ruya
    Gunal, Ayse Yeter
    3C TECNOLOGIA, 2023, 12 (01): : 125 - 146
  • [24] The clean analysis process of Mn2+ for industries: a comparative study on direct determination of high-concentration Mn2+ in solution using spectrophotometry
    Xu, Yanli
    Xu, Fuyuan
    Liu, Yong
    Zhu, Guangbin
    Chen, Ying
    Duan, Ning
    BMC CHEMISTRY, 2025, 19 (01)
  • [25] Optimisation and economic analysis of industrial-scale anaerobic co-digestion (ACoD) of palm oil mill effluent (POME) and decanter cake (DC) using machine learning models: A comparative study of Gradient Boosting Machines (GBM), K-nearest neighbours (KNN), and random forest (RF)
    Yang, Pang Bo
    Chan, Yi Jing
    Yazdi, Sara Kazemi
    Lim, Jun Wei
    JOURNAL OF WATER PROCESS ENGINEERING, 2024, 58