Real-time neuro-fuzzy controller for pressure adjustment in water distribution systems

Abstract

This work applied a neuro-fuzzy technique for real-time pressure control in water distribution systems with variable demand. The technique acted to control the rotation speed of the pumping system, aiming mainly at increasing energy efficiency. Fuzzy, neural and neuro-fuzzy controllers were tested in an experimental setup to compare their performances in a transient regime, a permanent regime, and with respect to disturbances applied to the system. To evaluate the efficiency of the system, a demand variation curve was emulated for different operating conditions. The results demonstrate that the neuro-fuzzy controller (NFC) presented a significant increase in pumping system efficiency and a reduction in specific energy consumption of up to 79.7% when compared to the other controllers. Target pressures were kept close to the set-point values with low hydraulic transients and maintained satisfactory stability (error <8%) under severe situations of demand variation. It is concluded that the NFC presented superior results when compared with the other analyzed controllers. HIGHLIGHTS A neuro-fuzzy controller for real-time pressure control of WDS is proposed.; The performance of the neuro-fuzzy controller is robust.; The effectiveness of controller has been demonstrated through experimental tests.; Improving the efficiency of pumping systems contributes to energy conservation.; Optimal pumping reduces up to 79.7% of the specific energy consumption.;

Keywords

• artificial intelligence
• artificial neural networks
• automation
• energy efficiency
• fuzzy logic
• water supply