Fuzzy control of nitrogen removal in predenitrification process using ORP

Area of Science:

• Environmental Engineering
• Wastewater Treatment Technologies
• Process Control

Background:

• Increasingly stringent wastewater discharge standards necessitate advanced nitrogen removal strategies.
• Fuzzy logic applications have shown promise in optimizing the activated sludge process.
• Predenitrification systems require effective control for sustainable nitrogen removal and reduced chemical usage.

Purpose of the Study:

• To present fuzzy control strategies for predenitrification systems to improve effluent quality.
• To investigate the reduction of chemical consumption through enhanced process control.
• To establish the correlation between nitrate concentration and ORP for on-line control.

Main Methods:

• Implementation of fuzzy control strategies in laboratory-scale predenitrification systems.
• Experimental investigation of the correlation between nitrate concentration and Oxidation-Reduction Potential (ORP).
• Utilizing ORP as an on-line control parameter for nitrate recirculation and external carbon addition.

Main Results:

• Established an excellent correlation between nitrate concentration and ORP at the end of the anoxic zone.
• Identified optimal ORP values for controlling nitrate recirculation (-86 ± 2 mV) and carbon addition (-90 ± 2 mV).
• Demonstrated the performance and stability of fuzzy controllers with real wastewater, even with external disturbances.

Conclusions:

• Fuzzy logic control, using ORP as a key parameter, effectively enhances nitrogen removal in predenitrification systems.
• The proposed control strategies lead to improved effluent quality and reduced chemical consumption.
• The developed integrated control structure offers a stable and robust solution for wastewater treatment challenges.