煤层气发动机空燃比PID迭代学习控制  

PID IterativeLearning Control of Air Fuel Ratio for a Coal-Bed Gas Engine

作　　者：张健[1] 滕勤[1] 左承基[1] 

机构地区：[1]合肥工业大学机械与汽车工程学院,安徽合肥230009

出　　处：《计算机仿真》2011年第3期211-214,253,共5页Computer Simulation

基　　金：国家自然科学基金资助项目(60474057)

摘　　要：煤层气发动机优化控制问题,对预混合双阀控制,煤层气发动机空燃比前馈控制查询表需要稳态标定试验得到,传统的方法是进行反复的测试和离线修正来获得最优控制数据。为了降低试验工作量及其耗费,提出了反馈信息在线校正前馈控制脉谱的方法,采用迭代学习控制技术,分别设计了PID和模糊自适应整定控制器。利用辨识的发动机稳态模型,研究了不同初始状态下两种学习控制器的收敛性能和稳态空燃比校正效果。仿真结果表明,模糊自适应整定PID学习控制算法具有较快的收敛速度和较小的学习误差,更适合煤层气发动机位置控制参数的在线应用。A feedforward control look-up table for a pre-mixed coal-bed gas engine with double valves control was derived from steady-state calibration testing.A traditional approach was to conduct repeated testing and off-line correcting to obtain the optimal control data.In order to reduce the amount of engine testing and related cost,a method of on line correcting feedforward control map based on feedback signal was presented,and the PID learning controller and the fuzzy adaptive tuning PID learning controller were designed using iterative learning control techniques,respectively.By means of identified steady state model of the engine,the convergence performance and the air fuel ratio correction effect of both learning controllers in different initial state were studied.The simulation results show that the fuzzy adaptive tuning PID learning control algorithm has higher convergence rate and smaller learning errors,and is much more suitable for online learning and adjusting position control parameters for the coal-bed gas engine.

关 键 词：煤层气发动机 空燃比 迭代学习控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TK437[自动化与计算机技术—控制科学与工程]