不确定性加工过程控制的发展与实例分析  

Control Evolution and Case Study for Uncertain Machining Processes

作　　者：姚锡凡[1] 姚小群[2] 刘璨[3] 葛动元[1] 

机构地区：[1]华南理工大学机械与汽车工程学院,广东广州510640 [2]东莞理工大学机电工程系,广东东莞523106 [3]湛江海洋大学机械工程系,广东湛江524001

出　　处：《应用基础与工程科学学报》2010年第1期177-186,共10页Journal of Basic Science and Engineering

基　　金：国家高技术研究发展计划(863计划)资助项目(2007AA04Z111)

摘　　要：切削加工过程的模型难以精确地获得,其模型不确定性和非线性造成加工过程控制困难,成为自动控制在加工过程中应用的瓶颈.文中分析了加工过程切削力模型的不确定性;讨论了经典控制、现代控制和智能控制对模型不确定性的处理手法及其局限性;探讨了非线性不确定加工过程的控制及其鲁棒性,并以模糊控制、基于信息熵优化的控制和多模态专家控制为例,在切削条件或模型发生变化情况下研究加工过程控制系统性能.研究表明,那些不依赖于数学模型的智能控制,可较好地处理加工过程的不确定性,为不确定性加工过程控制提供一条合适途径.Machining models are difficult to accurately obtain. The difficulties in control of mac processes come form the uncertainty and nonlinearity in cutting processes, and resuh in （he bottleneck for applying automatic control in machining. Uncertainty in cutting force models was analyzed. Methods to deal with model uncertainty with classical control, modem control and intelligent control theory and their limitations were discussed. Control of nonlinear uncertain machining process and system robustness were investigated, and the performances of mac process control systems were analyzed by taking fuzzy controllers, entropy-based optimal controllers and multi mode expert controllers or model variations. The results showed those as examples under time-varying cutting conditions intelligent controllers independent of mathematical models, could deal with the uncertainty in machining models, and provided a reasonable way to control of uncertain machining.

关 键 词：控制 加工过程 不确定性 鲁棒性 智能控制 

分 类 号：TP271.4[自动化与计算机技术—检测技术与自动化装置] TG68[自动化与计算机技术—控制科学与工程]