伺服機構如X-Y平台及CNC機台存在非線性現象和外部干擾，容易造成循跡控制精度下降。這其中又以摩擦力為多數X-Y運動平台及CNC機台中最常見之非線性外擾。有鑑於此，探討及鑑別各式摩擦力模型，並設計摩擦力補償架構以克服摩擦力對系統的影響，為本論文的研究主題之一。本論文比較數種摩擦力模型對摩擦力現象的抑制效果，同時建構LuGre與GMS摩擦力模型並比較其在低速補償與追蹤精度改善的效果。除了摩擦力之外，CNC機台亦存在有：背隙、參數鑑別不精確等現象。為了精準估測位置、速度與系統總干擾量，本論文另一研究主題為擴張狀態觀測器。將Model-based的互補式滑模控制器搭配本論文所提出之適應性PI滑模擴張狀態觀測器，不但可精準估測系統狀態，亦可將估測之系統總干擾量補償至系統，進而達到高精度循跡控制之訴求。為驗證本論文所提方法之可行性，本論文不僅以MATLAB軟體模擬，同時亦使用XY運動平台進行循跡控制實驗。實驗結果顯示，本論文所提之適應性PI滑模擴張狀態觀測器之估測精準度與回授補償效果皆優於其他擴張狀態觀測器架構。

The nonlinear phenomena and external disturbances often found in the servomechanisms such as X-Y tables and CNC machines may deteriorate the tracking accuracy. Among them, friction is the most common nonlinear external disturbance in the X-Y tables and CNC machines. Hence, one of the main research topics of this thesis is to explore and construct various friction models so as to design friction compensation schemes to overcome the influence of friction on the system. This thesis compares the effectiveness of several friction models in suppressing the adverse effects caused by friction. Both the LuGre and GMS friction models are constructed and their effectiveness on low speed compensation and tracking accuracy improvement are compared. In addition to friction, CNC machines often encounter phenomenon such as backlash and modelling inaccuracy. In order to accurately estimate position, velocity and total disturbance of the system, the extended state observer (ESO) is another research topic in this thesis. Combining the model-based complementary sliding mode controller with the adaptive PI sliding mode extended state observer (APISMESO) proposed in this thesis can not only accurately estimate the system states such as position and velocity, but also compensate the estimated total disturbance into the system so as to achieve the goal of high contour following accuracy. To verify the feasibility of the proposed approach, this thesis not only conducts MATLAB simulation, but also uses the X-Y table to perform contour following experiments. Experimental results show that the proposed adaptive PISMESO is superior to other ESO architectures in estimating accuracy and feedback compensation.

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