Study On Optimization Modeling And Intelligent Control Of Non-heated Regeneration Air Dryer

For a long time, traditional control methods of heatless regeneration air dryers caused a lot of problems such as energy waste of regeneration gas and decrease of aridity when the intake air temperatures is low and the pressure drops. The high reliability and remarkable energy-saving effect can be obtained by timely adjusting the time of adsorption, regeneration and pressure equalization based on the user's actual requirements of dew point and the change of operation conditions, and using of sensor technology and control technology for intelligent control of intake air temperatures and pressure parameters. In this paper, we deal with the optimal control of the regeneration gas quantity by the methods of functional analysis and adaptive variable metric particle swarm optimization, and intelligent control of the regeneration gas quantity, air temperatures and pressure by a combination controller based on the neuron fuzzy inference system. The main works of the paper is as follows:(1) The practical cost functional of regeneration gas consumption during regeneration is established. The consumption objective function of the regeneration gas quantity in unit time is optimized based on adaptive variable metric particle swarm optimization. The functional optimizer of the regeneration gas quantity is designed, which provides a theoretical basis for the online optimizing control and energy saving during regeneration.(2) A combination controller based on the neuron fuzzy inference system is designed. The simulation results show that the combination controller has good tracking performance, strong anti-interference ability, fast response and good robustness.(3) A PLC control system of heatless regeneration air dryers is developed. Then, the combination controller of the neuron fuzzy inference system is used to intelligent control the regeneration flow and process.The application results show that the electricity charge of air compressor dropped to 46,000 RMB from 53,000 RMB, and the cast of electricity charge will be reduced at least 15% every year when the functional optimizer of the regeneration gas consumption has been test run.