Sewage pumping stations control system based on fuzzy self-learning

The urban drainage system is complex. Flux and water lever of the system are affected by the people behaviors, rain and some other unpredicted factors such as channel leakage. But Sewage overflow may happen with improper control policy. And the system has the potential of saving power So a design of sewage pumping station fuzzy controller based on improved genetic algorithms is proposed And the mathematical model based on energy and network pollution minimizing is presented Improved genetic algorithms acquire the fuzzy rules of the fuzzy controller and optimize parameters. The design of fuzzy controller has been proved to have good robust with simulating calculation. Combining of the method proposed in this article with VVVF is more advanced than the traditional method with constant rate. Water level can keep unvarying at aimed water level and achieve that flux in equal flux out. It could achieve the double-optimal control goal of energy and pollution minimizing. Through simulating experiment, the system has good applied value.