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題名 | 適應性小波類神經網路於單缸膜片式氣壓隔振系統之控制=Adaptive Wavelet Neural Network Control for a Diaphragm-Type Pneumatic Vibration Isolator |
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作者 | 梁晶煒; 陳宏毅; 周彥騰; Liang, Jin-wei; Chen, Hung-yi; Chou, Yan-teng; |
期刊 | 應用聲學與振動學刊 |
出版日期 | 20141200 |
卷期 | 6:2 2014.12[民103.12] |
頁次 | 頁15-20 |
分類號 | 448.942 |
語文 | chi |
關鍵詞 | 單缸膜片氣壓隔振系統; 適應性小波類神經網路控制器; 學習能力; Diaphragm-type pneumatic vibration isolator; Adaptive wavelet neural network controller; Online learning ability; |
中文摘要 | 由於氣體的可壓縮性及氣壓系統孔口流等非線性之特性,使氣壓隔振系統具有時變與高度非線性,若要建立系統正確之數學模式是非常不容易的。所以本研究嘗試以類神經網路控制法則,來針對主動式氣壓隔振系統進行控制。類神經網路具有強大的學習能力,高度的容忍誤差、平行運算之學習能力等特性,故可用於非線性動態函數之近似。本研究以適應性小波類神經網路控制法則來進行控制器之設計,並針對主動式單缸膜片氣壓隔振系統進行控制。從實驗結果可以得知,本研究所設計之控制器在單缸膜片式氣壓隔振系統之控制中,可呈現明顯之隔振成效。 |
英文摘要 | It is well known that a pneumatic actuating system has nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the pneumatic actuating force. An intelligent control strategy for a diaphragm-type pneumatic vibration isolation system is developed in this research. In this paper, a model-free adaptive wavelet neural network (AWNN) controller is proposed to control a diaphragmtype pneumatic vibration isolator. This approach has online learning ability and the advantage to achieve the controller design without knowledge of the system dynamic model. In order to validate the proposed method, a composite control scheme using pressure and velocity measurements as feedback signals is implemented. Experimental results are executed to show the control performance of the proposed intelligent controller. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。