應用適應性史密斯控制器於工具機切削扭矩控制

在加工過程中，透過穩定切削力進行加工進給率最佳化不僅可以提升加工效率，亦可以保護刀具。許多研究提出不同的控制方法來進行進給率調變，然而，大部分研究將工具機切削動態進行簡化，忽略插補器與通訊延遲所造成的影響，進給率容易在加工條件改變時產生振盪或不穩定。在本文中，工具機切削動態拆分成四部分進行建模，分別為插補器、伺服傳動、切削模型以及通訊時間延遲。為了確保系統的強健性與克服通訊時間延遲，本文整合線上參數估測器(online parameter estimator)與史密斯預測器(Smith predictor)，提出適應性史密斯控制器(adaptive Smith controller)進行進給率的調變。線上參數估測器不僅可以反映切削條件的改變，亦可以估測刀具磨耗對切削模型的影響，使進給率控制器更加強健。為了驗證本文提出的控制架構能夠有效調變進給率，PI (proportional-integral)控制器、傳統史密斯控制器與適應性史密斯控制器分別用於切削三個不同切深的工件，而本文所提出的控制架構擁有最穩定的效果。同時，透過調整目標切削負載，相較於沒有進行進給率控制的結果，使用本技術進行進給率調變可以提升加工效率達10.5 %。

In machining processes, controlling the cutting force by optimizing the feedrate can not only enhance machining efficiency but also protect the cutting tool. Many studies have proposed various control methods for feedrate modulation. However, most studies simplify the dynamics of the cutting process, neglecting the effects of the interpolator and communication delay, which can cause oscillations or instability when machining conditions change. In this article, the dynamics of the cutting process are modeled using four components: the interpolator, servo drive system, cutting model, and communication time delay. To increase system robustness and compensate for communication time delay, this research proposes an adaptive Smith controller, which integrates an online parameter estimator with a Smith predictor to modulate the feedrate. The online parameter estimator can not only reflect changes in cutting conditions but also estimate the effect of tool wear on the cutting model, thereby enhancing the robustness of the feedrate control. To verify the effectiveness of the proposed control architecture for feedrate modulation, three different control strategies were compared: a proportional-integral (PI) controller, a conventional Smith controller, and the adaptive Smith controller. The proposed control architecture demonstrated the most stable performance. By adjusting the reference cutting torque, the proposed control architecture could improve machining efficiency by 10.5 % compared to scenarios without control.