A chemical process fault monitoring algorithms based on kernel entropy component analysis(KECA) is presented for the complexity and nonlinear of industrial chemical process data. The number of principal components sel...
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A chemical process fault monitoring algorithms based on kernel entropy component analysis(KECA) is presented for the complexity and nonlinear of industrial chemical process data. The number of principal components selected by the KECA algorism is much less than the KPCA algorism. This is achieved by selections onto eigenvalue and eigenvector based on the value of Renyi Entropy. research shows that KECA reveals angular structure relating to the Renyi entropy of the input space data set. A new statistic, namely the cosine value between vectors in kernel space, is proposed, which describes the similarity between different pdfs(probability density functions). It is shown that KECA has great advantages in detection latency and fault detection rate in comparing to KPCA by applying them to TE(Tennessee Eastman) process respectively.
Aiming at the DC injection of grid-connected inverter, the grid-connected inverter with LCL filter is studied and a strategy of current tracking control is presented to suppress its DC component, which adopts the dual...
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Aiming at the DC injection of grid-connected inverter, the grid-connected inverter with LCL filter is studied and a strategy of current tracking control is presented to suppress its DC component, which adopts the dual closed loop technique to directly control the grid-connecting current. A DC component suppression branch consisting of an integral controller is added to the conventional fundamental current control branch in the outer current-loop, which increases the DC output impedance of inverter to suppress its DC component, without affecting the fundamental current tracking control. The implementation of the proposed strategy is simple because, without DC component detection, only the virtual impedance is connected in series to the output port of inverter, which is infinite to DC component while small to AC frequency. A model is built and the frequency domain analysis proves its DC inhibition performance. The simulative and experimental results show that, the fundamental reference tracking with zero steady-state error is realized and the DC component is well suppressed. Electric power Automation Equipment Press
The small sample prediction problem which commonly exists in reliability analysis was discussed with the progressive prediction method in this *** modeling and estimation procedure,as well as the forecast and confiden...
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The small sample prediction problem which commonly exists in reliability analysis was discussed with the progressive prediction method in this *** modeling and estimation procedure,as well as the forecast and confidence limits formula of the progressive auto regressive(PAR) method were discussed in great *** model not only inherits the simple linear features of auto regressive(AR) model,but also has applicability for nonlinear *** application was illustrated for predicting the future fatigue failure for Tantalum electrolytic *** results of PAR model were compared with auto regressive moving average(ARMA) model,and it can be seen that the PAR method can be considered good and shows a promise for future applications.
The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with mode- dependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensure...
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The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with mode- dependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.
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