A Comparative Study of State Estimation Methods for Processes with Asynchronous and Delayed Measurements

被引：0
作者：
Mejia-Estrada, Eliana [1 ]
Botero-Castro, Hector [2 ]
Isaza-Hurtado, Jhon A. [2 ]
机构：
[1] Univ Nacl Colombia, Grp Automat Univ Nacl GAUNAL, Sede Medellin, Carrera 80 65-223, Medellin, Colombia
[2] Univ Nacl Colombia, Grp Invest Proc Dinam Kalman, Sede Medellin, Carrera 80 65-223, Medellin, Colombia
来源：
2017 14TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTING SCIENCE AND AUTOMATIC CONTROL (CCE) | 2017年
关键词：
Batch process; Cascade observer-predictor; delta-endotoxins production of Bacillus thuringiensis; Extended Kalman Filter; Fixed Lag Smoothing; Second order sliding mode algorithm; Smith predictor; KALMAN FILTER; IMPLEMENTATION; INFREQUENT; SYSTEMS; FUSION;
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：
This paper presents a comparison between two state estimation methods for processes with asynchronous and delayed measurements in order to verify which of these techniques is better in terms of dynamic behavior and possibilities of implementation in a real time processor. The methodologies are analyzed through simulations that allow a comparison in a visual form, through error index and with the time of computational load. The analyzed estimators consists in a cascade observer-predictor algorithm where the observer stage is based on a second order sliding mode algorithm, followed by a Smith predictor and the second one is based on the Kalman filter with augmented state space using the fixed-lag smoothing method. These estimators were applied on a batch bioprocess used in the production of delta-endotoxins of Bacillus thuringiensis.
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页数：6
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