在聚酯(Polyester，PET)膜的捲取過程，一般是藉由羅拉或滾輪做為傳輸與控制的設備，在業界又稱為Roll-to-Roll設備。捲取過程中，理想的動態行為應僅有縱向方向的動態，但實際上因為羅拉之間架設的不平行、橫向上的干擾、不穩定的線速度與張力控制以及PET薄膜本身所造成的振動，這些因素會使PET薄膜產生橫向偏移，當PET薄膜產生橫向偏移時會導致產品品質的降低產生瑕疵，例如：貼合不良、分條不均、收捲不齊、捲邊、皺折、印刷歪斜等，使得原料的浪費並可能對製程中的設備造成損害。本文主旨將針對聚酯膜於三羅拉兩間距的系統上，產生的橫向偏移量加以分析與控制，以期望橫向偏移量能抑制在允許公差內。由於聚酯膜受到前段製程及系統內橫向的隨機干擾，使得聚酯膜在收捲端位置的橫向偏移呈現極不穩定的情形，因此採用自調式類神經PID控制器與高增益輸出回授適應性控制器，因為此兩種控制器對於外在干擾皆具有良好強健性與適應性。自調式類神經PID控制器，以現今業界應用最廣泛的PID控制器為主控制器，藉由倒傳遞類神經的學習方法調整PID控制器的增益參數，使增益參數能依據系統的狀態適時的做線上調整，以增強控制器的自調性與強健性；高增益輸出回授適應性控制器，為非基於鑑定(Non-Identifier-Based)方法的適應性控制，利用線上調整回授增益的方式，使得控制器具有良好的適應性，而此方法在過去常被應用在衰減干擾、系統參數變動與抑制系統不確定性。最後在實驗中，將PET膜架設於所建構的系統上，由於PET膜在系統內受到隨機性的干擾，使得在收捲端位置造成橫向偏移，因此利用自調式類神經PID控制器與高增益輸出回授適應性控制器，加以導正收捲端位置的橫向偏移量，其結果可證明所提出的兩種控制器皆可有效降低干擾對於橫向偏移量的影響，並導正PET膜的橫向偏移得到良好的控制效果。

In the winding process of polyester (PET) films, the PET film is conveyed through a system of rollers or cylinders that supply support, transport, and control. This kind of conveyance is called a roll-to-roll apparatus. Ideally, the motion of the PET film winding process is only in a longitudinal direction. This is not the case for real conveyance systems since misalignment of rollers, lateral disturbances, unsteady speed and tension, and the films physical properties result in lateral deflection of the PET film. This lateral deflection may lead to the downgrade of product quality and material waste, damage the equipment, and produce material defects such as illegal laminating, uneven edge of slitting, slack selvedge in winding, crimping, winkle, and slant on painting, etc. The material of PET films is adopted, and the winding system is constructed by a three-roller two-span mechanism for experiments. The main objective of this thesis is to analyze and control the lateral deflection so that the lateral deflection is within the required tolerance in the winding process. In this thesis, we adopted the self-tuning neuro-PID controller and adaptive high-gain output feedback controller because the indeterminate disturbances exist in the system. Both controllers possess robustness and adaptability. The self-tuning neuro-PID controller is used to self tune the parameters of the PID controller by the backpropagation neural network method, which is based on the deviation of the output response to a target. The self learning feature of the neural network can be exploited in autotuning the PID gain parameters. The adaptive high-gain output feedback controller can tune the high-gain parameters online, which is not based on any parameter identification or estimation algorithm. This controller works well on disturbance rejection, parameter variations and system uncertainty. The investigation was tested through the computer simulation and experiments for its validity. We set up the PET film on the designed mechanism. There exists stochastic lateral disturbances in the process that cause the lateral deflection of the moving PET film. Then, the self-tuning neuro-PID controller and adaptive high-gain output feedback controller are designed to guide the lateral deflection. The results reveal that the controllers provide good guiding performance for lateral deflection and to reduce substantially the effect of disturbances on the lateral defection of winding PET films.

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