本文選題：網絡控制系統(tǒng)　切入點：相空間重構　出處：《電子學報》2017年05期 　論文類型：期刊論文

【摘要】：針對網絡控制系統(tǒng)的時延預測問題,提出一種基于相空間重構與最小二乘支持向量機的時延預測方法.首先利用0-1測試法確定時延序列具有混沌特性,引入相空間重構技術提高預測精度.對實際采集的時延序列進行Hurst指數分析,選擇最小二乘支持向量機作為預測模型.然后利用C-C方法確定時延序列相空間重構參數,通過遞歸圖確定時延序列的局部可預測性,利用遺傳算法對最小二乘支持向量機的參數進行離線優(yōu)化.最后通過優(yōu)化后的最小二乘支持向量機并結合相空間重構對時延序列進行在線預測.與其它預測方法進行了仿真對比,結果表明本文方法具有更高的預測精度與更小的預測誤差,同時并未降低預測算法的實時性.
[Abstract]:For the networked control system with time delay prediction problems, put forward a prediction method of phase space reconstruction and least squares support vector machine based on the time delay. First determine the delay time series has chaotic characteristics by using the 0-1 test method, the phase space reconstruction technique to improve the prediction accuracy. The Hurst index analysis of the actual delay sequence collection, selection of the least squares support vector machine as the prediction model. Then use the C-C method to determine the parameters of phase space reconstruction delay sequence through recursive delay sequence diagram to determine local predictability, off-line optimization of the parameters of least squares support vector machine using genetic algorithm. Finally, the optimized least square support vector machine combined with phase space reconstruction is applied to the online prediction of the delay time series. Compared with other forecast methods, the results show that this method has higher prediction accuracy and smaller The prediction error does not reduce the real-time performance of the prediction algorithm.

【作者單位】： 沈陽工業(yè)大學信息科學與工程學院;東北大學計算機科學與工程學院;
【基金】：國家自然科學基金(No.11273001) 遼寧省博士啟動基金(No.20141070)
【分類號】：TP18;TP273

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1 馬東玲;;相空間重構中時間延遲的確定方法[J];硅谷;2013年19期

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本文編號：1601201