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Active Disturbance Rejection Control (ADRC) is a quiet different design concept that shows much promise in obtaining a consistent response in a control system with many uncertainties. For the lack of frequency-domain analysis, in this paper, starting from the frequency domain methods, the tracking ability of linear extended state observer (LESO) and the disturbance rejection quality of linear ADRC...
This paper puts forward a design which is presented to estimate relatively accurate HAGC control system and then to predict the rolling gap. Considering many factors that influence the precision of the rolling gap, we can obtain the final formula of the rolling gap according to the theoretical calculation. Besides, A SVM (support vector machine) regression model based on the machine learning is proposed...
In electricity, resistance R and capacitor C are common components, and also are indispensable. The circuit with R and C looks simple, but in a sense, it shows some physical phenomenon behaviors. In this paper, we take RC system as the example, and implement control of the different series RC system with only using the second-order linear Active Disturbance Rejection Controller (ADRC). The simulation...
To solve the problem of roll eccentricity signal with the noise in the HAGC system, a new method based on adaptive threshold de-noising algorithm of roll eccentricity signal is proposed. The new method can self-adaptively decide the threshold of wavelet analysis and make the SNR as a function of the parameter of the filter to acquire the optimal threshold parameter by using midpoint method. This method...
A novel methodology based on V-system polynomials for content-based search and retrieval of 3D objects is proposed and implemented in the experiment with the contest's query set and the model database. By the benchmark of the SHREC'06 to the algorithm, this method shows highly performance and improves the retrieval efficiency.
In this paper, a forward neural network (FNN) is used for 3D model retrieval. Also the descriptor based on exponentially decaying Euclidean distance transforms (EDT) is adapted to represent the feature of a 3D model. As a kind of machine learning method, FNN is trained by the PSB trained data, and then used to sort the testing data set in this contest.
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