【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.更多还原

【Abstract】 Machining models are difficult to accurately obtain.The difficulties in control of machining processes come form the uncertainty and nonlinearity in cutting processes,and result in the bottleneck for applying automatic control in machining.Uncertainty in cutting force models was analyzed.Methods to deal with model uncertainty with classical control,modern 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 machining process control systems were analyzed by taking fuzzy controllers,entropy-based optimal controllers and multi mode expert controllers as examples under time-varying cutting conditions or model variations.The results showed those intelligent controllers independent of mathematical models,could deal with the uncertainty in machining models,and provided a reasonable way to control of uncertain machining.更多还原