linear time-varying network 中文意思是什麼
linear time-varying network
解釋
線性變參數網路-
The primary works and innovations of this paper include but not limited to : ( 1 ) considering the nonlinear, time - varying and uncertain characteristics of networks, a new active queue management ( aqm ) algorithm, i. e. nnpc - aqm was proposed based on predictive control theory, which requires less model accuracy. in order to realize fast control, a predictor was constructed using two - layer linear neural network to predict the future queue length, and a controller was composed using two layers of nonlinear neural network to optimize the next control volume, i. e. drop probability
本文研究的主要內容及創新點如下： （ 1 ）針對網路的非線性、時滯、不確定特點，結合預測控制理論提出一種新型主動隊列管理（ aqm ）策略nnpc - aqm ，該演算法基於單值預測控制思想，為了實現快速控制，採用兩層神經網路構造預測器，估計未來時刻隊列長度；採用兩層非線性神經網路組成控制器，實現對下一步丟棄概率的優化。 -
( 2 ) wavelet networks are introduced to gpc. several nonlinear gpc algorithms based on wavelet networks are given : a nonlinear gpc base on predictive error compensation is designed, in which wavelet network is used to model the predictive error ; a new structure of multi - step predictive controller is constructed in which wavelet networks are used to identified the nonlinear directly ; a single - step predictive controller is given, in which a wavelet networks are used to estimate the parameters of the linear time - varying system. ; an a implicit gpc for nonlinear system is presented, in which wavelet networks are used to estimated the time - varying parameters of the generalized predictive controller
（ 2 ）將小波網路與非線性廣義預測控制相結合，設計了多種基於小波網路的非線性廣義預測控制：考慮到建模誤差對多步預報的影響，引入小波網路估計預報誤差，對輸出預報進行修正，提高了控制性能且不影響系統的穩定性；利用小波網路構造多步預測器，設討了非線性系統多步預測控制演算法；利用小波網路逼近非線性系統廣義預測控制器的時變參數，設計了非線性系統隱式廣義預測控制器；利用小波網路辨識時變系統參數並直接用於構造控制器，設計了非線性系統單步預測控制演算法。 -
This method can guarantee the solution matrix of sylvester equation to be inverse and the sum of the input gain norm and the observer gain norm is the minimum. for the linear systems with unknown parameters, we identify the parameters using hopfield network, then design the observers using the identified parameters, the exponential convergence of adaptive observer is also proved. for the linear time - varying systems, a new network to solve the time - varying sylvester equation is proposed, we analysis it ' s convergence and robustness, then, deign the linear time - varying observer using this network model, and we discuss the convergence of the observer and ruboustness to unknown match parameters
同時保證了sylvester方程的解矩陣的可逆性和觀測器的增益矩陣與輸入矩陣范數的和最小；在設計線性時不變自適應觀測器時，首先利用系統的輸入、輸出數據設計一個hopfield網路參數估計器，進一步設計狀態觀測器，證明了參數估計器和狀態觀測器的指數收斂性；為了仍然從神經優化計算的角度設計線性時變系統的狀態觀測器，最後介紹了一種求解時變sylvester矩陣方程的神經網路模型，分析了它的收斂性和魯棒性，然後利用該網路設計時變狀態觀測器，進一步討論該觀測器的在系統存在未建模不確定和外部噪聲時的魯棒性；最後給出了一種基於分離性原理和hopfield網路觀測器的狀態反饋閉環系統的結構，分析了該閉環系統的特點；對于每一種設計方法都給出了相應的數值模擬例子來進一步表明所提方法的可行性和有效性。
分享友人