Complete Control System  

Complete Control System  

Source publication
Article
Full-text available
In the actual control, complete differential digital PID algorithms have been widely used. But the differential will amplify high-frequency noise. If the differential response is too sensitive, it is easy to cause the control process oscillation, incomplete PID control algorithms can overcome the differential oscillation. Incomplete derivative PID...

Context in source publication

Context 1
... differential PID [10] controller is a linear combination of the regulator in accordance with the error, integral of error, differential error. Figure 1 shows a complete differential PID controller block diagram. ...

Similar publications

Conference Paper
Full-text available
Glomerulus classification in kidney tissue segments is a key process in nephropathology to obtain correct diseases diagnosis. In this paper, we deal with the challenge to automate the Glomerulus classification from digitized kidney slide segments using a deep learning framework. The proposed method applies Convolutional Neural Networks (CNNs) class...
Conference Paper
Full-text available
Effects of in-plane and out-of-plane loading are generally observed separately, but recent investigations are trying to combine the influence of in-plane damage on out-of-plane strength. In this paper, out-of-plane effects caused by in-plane loading are determined through digital image correlation. Based on conducted experimental research with vari...
Conference Paper
Full-text available
Massive MIMO systems are now well known for their energy efficiency. The ability to focus the energy to a targeted user not only increases the gain of useful signal but also reduces inter-user interference to the point where Spatial Division Multiple Access becomes possible. Using such systems at high frequencies, thus greatly reducing the array fo...
Research
Full-text available
This paper presents a new robust digital image watermarking technique based on relation between wavelet transform coefficients and neural network. The neural network used in this thesis, is MLP (Multi-Layer Perceptron).