Interval Type-2 Fuzzy Observers Applied in Biodegradation
Open Access
- 7 May 2021
- journal article
- Published by ASCEE Publications in International Journal of Robotics and Control Systems
- Vol. 1 (2), 145-158
- https://doi.org/10.31763/ijrcs.v1i2.344
Abstract
There exist processes difficult to control because of the lack of inline sensors, as occurs in biotechnology engineering. Commonly the sensor is expensive, damaged, or even they do not exist. It is important to build an observer to have an approximation of the process output to have a closed-loop control. The biotechnological processes are nonlinear, thus in this work is proposed a fuzzy observer to endure nonlinearities. To improve the results reported in the literature, type-2 fuzzy logic was used to justify the membership functions used. The observer's gains were computed via LMIs to guarantee the observer's stability. To facilitate the fuzzy inference computation, interval type-2 fuzzy sets were implemented. The results obtained with the interval type-2 fuzzy observer were compared with a similar technique that uses a fuzzy sliding mode observer; this new approach gives better results obtaining an error 60% lower than the obtained with the other technique. They were designed three observers that work ensemble via a fuzzy relation. The best approximation was to estimate the intermediate concentration. It is important to know this variable because this sub-product was also toxic. It was concluding that by using the oxygen concentration and the liquid volume inside the reactor, the other concentrations were estimated. Finally, this result helps to design a fuzzy controller by using the estimated state. Using this approach, the estimation errors for the phenol and biomass concentrations were 49.26% and 21.27% lower than by using sliding modes.Keywords
This publication has 18 references indexed in Scilit:
- Stable fuzzy control and observer via LMIs in a fermentation processJournal of Computational Science, 2018
- An Adaptive Observer Design for Takagi-Sugeno type Nonlinear System * *The work was supported by FP7 project Energy in Time (EiT) under the grant no. 608981IFAC-PapersOnLine, 2017
- Fuzzy iterative learning control applied in a biological reactor using a reduced number of measuresApplied Mathematics and Computation, 2014
- Stability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy ModelsPublished by Springer Science and Business Media LLC ,2011
- Fuzzy Logic with Engineering ApplicationsPublished by Wiley ,2010
- Type-2 Fuzzy Logic: Theory and ApplicationsPublished by Springer Science and Business Media LLC ,2008
- Fuzzy Model Based Iterative Learning Control for Phenol BiodegradationLecture Notes in Computer Science, 2007
- Biomass and Phenol Estimation Using Dissolved Oxygen MeasurementPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Two-step modeling of the biodegradation of phenol by an acclimated activated sludgeChemical Engineering Journal, 2006
- Fuzzy Modeling for ControlPublished by Springer Science and Business Media LLC ,1998