Investigation Of Sensor Dynamic Test System Based On Optimized Fuzzy PID Gas Flow Control

The precision of gas sensor test system is crucial for meeting the booming sensor market.For a gas sensor test system,a series of performance indicators(e.g.,response value,response time,recovery time,etc.)can be presented when we test a gas sensor.These indicators are vulnerable under specific conditions,such as fluctuated velocity of gas flow,temperature and humidity etc.Especially,there will be nonnegligible drift of output signal when the velocity of gap flow changes,which directly reveals the performance of the gas sensor.However,three issues,i.e.,slow responding speed,susceptible output signal and low capability for controlling the micro-gas flow for the usual gas sensor dynamic test system,seriously affects its test performance.Given above problems,in this project,we therefore proposed a fuzzy self-tuning PID micro gas flow control method based on optimized particle swarm optimization algorithm,and investigated the technology of the high-efficient and high-precise gas flow control based on our designed semiconductor gas sensor dynamic test system that integrating above gas flow control method.Our main findings are as follows:1.The structure topology of gas flow control is established by analyzing the influence of gas flow rate on the performance test of semiconductor gas sensor.The test principle of the gas sensor and the influence of the gas flow rate on the performance of the gas sensor are analyzed.The problems of gas flow rate in conventional gas sensor test systems are elaborated.Based on the analysis of the properties and detection methods of micro gas flow,the overall scheme design,gas path structure topology and hardware circuit design of semiconductor sensor dynamic test system based on gas flow control are proposed.2.Fuzzy self-tuning PID control algorithm is intensively studied and the parameters of conventional incremental PID gas flow controller are self-tuned byusing fuzzy control.The small gas flow closed-loop control system is a complex nonlinear system with many uncertainties and cannot be described by classical binary logic.A single control method is difficult to meet the actual needs.Moreover,the conventional gas flow PID control parameters are cumbersome and often fail to achieve the desired results.In order to make the gas flow through the gas sensor quickly and steadily,the design of the fuzzy controller is completed on the basis of many practical operations and the routine PID parameter tuning.The mathematical model of the gas flow is obtained through system identification.A fuzzy self-tuning PID micro-gas flow control simulation model was built.3.The improved particle swarm optimization algorithm is used to automatically optimize the fuzzy factor of the gas flow fuzzy control system,and the performance of the fuzzy controller is optimized.The third chapter completes the design of the gas flow fuzzy controller.During the simulation and actual operation,it is found that the fuzzy factor has a great influence on the gas flow fuzzy controller and the output of the entire control system.Therefore,it is necessary to further optimize the fuzzy factor in the gas flow fuzzy control system.In this paper,the particle swarm optimization algorithm based on nonlinear decreasing inertia weight(NDWPSO)is used to optimize the fuzzy self-tuning PID gas flow control scheme design.The PID gas flow control,fuzzy self-tuning PID gas flow control and improved particle swarm optimization fuzzy self are established.A comparative simulation model for tuning PID gas flow control.Improved particle swarm optimization algorithm improves the convergence speed and optimization accuracy of the basic particle swarm optimization algorithm and overcomes the shortcomings of the basic particle swarms being easy to fall into local optimum.The result of improved particle swarm optimization algorithm guides the hardware implementation of STM32 as the main control unit.Finally,our test results of the gas flow control show that the fuzzy self-tuning PID gas flow control adjustment time based on the improved particle swarm optimization algorithm is only 1-3 seconds,which is less than 85% comparing toconventional PID gas flow control.And the control accuracy is ± 10ml/min,the resolution is 1ml/min,not over-adjusted output,high steady signal.Therefore,the gas flow fuzzy self-tuning PID control optimized by the improved particle swarm optimization algorithm has strong robustness and fast response speed,which makes the micro-gas flow control achieve fast and steady output signal.Our study provides technical support for high-precision dynamic testing of gas sensor performance.