Aeration control by monitoring the microbiological activity using fuzzy logic diagnosis and control. Application to a complete autotrophic nitrogen removal reactor

Boiocchi, Riccardo; Mauricio‐Iglesias, Miguel; Vangsgaard, Anna Katrine; Gernaey, Krist V.; Sin, Gürkan

doi:10.1016/j.jprocont.2014.10.011

Cited by 20 publications

(8 citation statements)

References 18 publications

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“…The neuron network, for example, is used to remove noises from defected image (Sagiroglu and Besdok, 2012); the trajectory control application in robot manipulators is carried out using fuzzy (Sliding Mode Control) SMC with radial basis function neural network (Ayça Gokhan et al, 2015). And in Boiocchi et al (2015), the authors performed the diagnosis and control using fuzzy logic.…”

Section: • • Bearing Faults (40%);mentioning

confidence: 99%

Fault diagnosis in yaw drive induction motor for wind turbine

et al. 2018

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Wind turbines are widely exploited throughout the world. The availability and reliability of offshore wind turbines are asking to impose a constant maintenance strategy. In this work, we propose a method that allows filtering the signal of the frequency inverter that feeds the yaw drive used in wind turbine. The redundant information is eliminated via discrete wavelet transform and empirical modal decomposition. The two types of faults are detected from the envelope of the Hilbert transform. The magnitude imbalance detection is carried out in the time domain. The root mean square values of the envelopes of the threephase system have a good indicator for the fuzzy system to evaluate the severity of the defect. In the frequency domain, the signature of the broken bar fault is located in the low-frequency bandwidth. The harmonics appeared in the spectrum sensitive in amplitude and frequency to the variation of load. Experimental results have demonstrated the accuracy of the proposed method.

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Section: • • Bearing Faults (40%);mentioning

confidence: 99%

Fault diagnosis in yaw drive induction motor for wind turbine

et al. 2018

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“…The liquid level and flow control between two or more tanks are substantial application in many industrial areas such as power generation, 1 biochemical, 2 petrochemical processing, water distribution. 3 In these industries, the liquid can be stored in a tank, pumped into another tank or mixed with chemical liquids.…”

Section: Introductionmentioning

confidence: 99%

Real-time implementation of self-tuning regulator control technique for coupled tank industrial process system

Ayten

Dumlu

Kaleli

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article presents the self-tuning regulator control technique for a coupled tank liquid level system that often used in industry. An autoregressive with exogenous model has been used as the liquid process model with the self-tuning control implementation in order to track the desired tank level trajectories with disturbances and uncertainties of the system dynamics. The designed self-tuning controller has been sensitive to parameter variations of the nonlinear coupled tank system. The parameters of the proposed controller are periodically updated themselves during the process by means of online recursive least square method with the forgetting factor algorithm. In this way, the parameter variations and unwanted disturbances of the system are eliminated in real-time application. In order to demonstrate the efficiency of the self-tuning regulator control technique, the real-time studies have been executed. The obtained experimental results demonstrated that the proposed controller gives the better trajectory tracking performance and smaller magnitude in overshot and undershot than the designed classical proportional–integral and sliding mode controllers.

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“…The liquid level and flow control between two or more tanks are a substantial application in many industrial areas such as power generation (Meribout et al, 2017), biochemical (Boiocchi et al, 2015), petrochemical processing, water distribution (Sankar et al, 2015; Xue et al, 2013) and so on. In these industries, the liquid can be stored in a tank, pumped into another tank or mixed with chemical liquids.…”

Section: Introductionmentioning

confidence: 99%

A combined control approach for industrial process systems using feed-forward and adaptive action based on second order sliding mode controller design

Dumlu

Ayten

2018

Transactions of the Institute of Measurement and Control

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This paper presents a new method that uses a feed-forward adaptive second order sliding mode control (FF-ASSMC) for a coupled tank process system that is often used in industry. This proposed method is to combine a feedforward action with adaptive feedback for robust performance of the couple tank system for the first time. The reason for using this feedforward action with the feedback sliding mode control (SMC) is to reduce the effect of the measured disturbance on the coupled tank system. In addition to this, an adaptive second-order SMC proposes to track the desired tank’s level trajectories under disturbances and uncertainties. In order to illustrate the efficiency of the proposed FF-ASSMC method, the simulation and real time experimental studies have been realized. The simulation and experimental outcomes strongly verified that the proposed controller gives a quite successful trajectory tracking response and smaller magnitude overshot under external disturbances.

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Aeration control by monitoring the microbiological activity using fuzzy logic diagnosis and control. Application to a complete autotrophic nitrogen removal reactor

Cited by 20 publications

References 18 publications

Fault diagnosis in yaw drive induction motor for wind turbine

Fault diagnosis in yaw drive induction motor for wind turbine

Real-time implementation of self-tuning regulator control technique for coupled tank industrial process system

A combined control approach for industrial process systems using feed-forward and adaptive action based on second order sliding mode controller design

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