The hybrid group consensus of multi-agent systems that consist of two groups in environments with time-delays and additive noises is studied in this *** hybrid group consensus implies that the agents in one group achi...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
The hybrid group consensus of multi-agent systems that consist of two groups in environments with time-delays and additive noises is studied in this *** hybrid group consensus implies that the agents in one group achieve strong consensus and the agents in another group achieve weak consensus.A new type of control protocol is proposed to achieve the following hybrid group consensus behavior:the agents in the first group and in the second group achieve strong consensus and weak consensus,*** sufficient conditions are obtained for the hybrid group consensus problem in both mean square and almost sure ***,a simulation example is given to illustrate the feasibility of the theoretical results.
In industrial processes,valve stiction often induces loop oscillations,and limits the control loop *** better control the plant with valve stiction,in this paper,the equivalent-input-disturbance（EID） approach is inc...
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ISBN:
(纸本)9781538629185
In industrial processes,valve stiction often induces loop oscillations,and limits the control loop *** better control the plant with valve stiction,in this paper,the equivalent-input-disturbance（EID） approach is incorporated into the conventional PID control system to improve the ability of disturbance and nonlinearity *** newly proposed method uses a classic two-parameter stiction model to represent the nonlinearity of valve *** to the EID method,an EID estimator is constructed to estimate the influence of valve stiction on the system *** controller is based on the basic proportional-integral-derivative（PID） *** a simulation example is provided to demonstrate the validity of this method.
The objective of this paper is to design an extended dissipative controller for drill-string systems by taking into account input time-delays. A multi-degree-of-freedom lumped parameter model is established for the dr...
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ISBN:
(纸本)9781728123295;9789881563972
The objective of this paper is to design an extended dissipative controller for drill-string systems by taking into account input time-delays. A multi-degree-of-freedom lumped parameter model is established for the drill-string and a state space model in perturbation coordinates is derived correspondingly. By using the Lyapunov-Krasovskii functional method, two sufficient conditions are provided to make extended dissipativity analysis of the drill-string and design a suitable extended dissipative controller for the system. The effectiveness of our results is verified through a numerical example.
The presence of stiction in a control valve causes loop oscillation,and limits the control loop *** address this problem,the paper proposes a method based on equivalent-input-disturbance（EID） to control valve *** th...
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ISBN:
(纸本)9781509046584
The presence of stiction in a control valve causes loop oscillation,and limits the control loop *** address this problem,the paper proposes a method based on equivalent-input-disturbance（EID） to control valve *** this method,a classic two-parameter stiction model is ***,an EID estimator is utilized to estimate the effects of valve stiction in control *** the controller is designed in the spirit of repetitive *** simulation control results are compared with the traditional *** results demonstrate that the proposed EID method can effectively improve the control performance of valve stiction and eliminate the stiction-induced oscillations.
The occurrence of landslide is uncertain, and its surface displacement data is an important physical quantity reflecting the occurrence process of landslide. Therefore, we propose a visual based small displacement lan...
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In the cement production process, the speed of grate coolers directly affects the residence time and cooling effect of cement clinker. Its effective control is of great significance to ensuring cement quality. But the...
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High accurate rate of street objects detection is significant to realize intelligent vehicles. Algorithms based on Convolution Neural Network (CNN) have already shown their reasonable performance on general object det...
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High accurate rate of street objects detection is significant to realize intelligent vehicles. Algorithms based on Convolution Neural Network (CNN) have already shown their reasonable performance on general object detection. For example SSD and YOLO can detection wide variety of objects on 2D images in real time, but the performance is not good enough on street objects detection especially on complex urban street environment. In this paper, instead of proposing and training a new CNN model, we use transfer learning methods to learn from generic CNN model to our specific model to achieve good performance. The transfer learning methods include fine-tuning the pretrained CNN model with self-made dataset and adjusting CNN model structure. We analyze transfer learning results on fine-tuning Single shot multibox detector (SSD) with self-made datasets. The experimental results based on transfer learning method show that the proposed method is effective.
Spectrum-induced polarization (SIP) is a widely used geophysical exploration approach, but it is prone to noise. To address this issue, this paper proposes a noise reduction method that combines phase space reconstruc...
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In the cement production process, the decomposer outlet temperature control faces challenges such as large time delay and multiple disturbances. A general control system cannot handle time delay and disturbances effec...
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Compared with speech, facial expression, and body languages, Electroencephalogram (EEG) can reflect the inner activity of brain, by which the emotion can be recognized objectively and naturally. In this paper, an EEG ...
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Compared with speech, facial expression, and body languages, Electroencephalogram (EEG) can reflect the inner activity of brain, by which the emotion can be recognized objectively and naturally. In this paper, an EEG emotion recognition system is proposed in which EEG signals of 6 channels are detected from Frontal Lobe and Temporal Lobe, and then the time-domain features of statistics features and frequency-domain features of spectrum centroid (SC) are extracted. To remove the redundant feature, Linear Discriminant Analysis (LDA) is used to reduce the dimension of feature. In addition, an improved classifier based on PSO-SVM is applied to classify the emotional states in the Valance-Arousal emotion model, respectively, which are defined as High-Valance (HV) and Low-Valance (LV) on the Valance dimension and High-Arousal (HA) and Low-Arousal (LA) on the Arousal dimension. EEG emotion recognition experiment on DEAP dataset is performed, from which the results show that the proposed method obtains the accuracies of 73.33% on Valance dimension and 72.78% on Arousal dimension, which are higher than those of some state-of-the art works.
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