Blast furnace operating parameters regulate the gas utilization rate (GUR), and different operating parameters affect the GUR on different time scales. However, the existing methods only analyze and model the predicti...
Blast furnace operating parameters regulate the gas utilization rate (GUR), and different operating parameters affect the GUR on different time scales. However, the existing methods only analyze and model the prediction on a single-time scale, and the accuracy of the model needs to be improved. In this paper, a multi-time-scale prediction method of blast furnace gas utilization rate based on causality is proposed. Firstly, according to the production characteristics of the blast furnace, burden and blast supply are the operation means to regulate the blast furnace on different time scales. Then, this paper presents a blast furnace operation parameter extraction method fusing correlation coefficient and information entropy, and selects two most informative parameters to characterize the operation. On this basis, the causal analysis method is used to prove that the selected operation parameters affect the development trend of GUR. Finally, the long and short time scale prediction models of GUR are established, which are verified by the data of the actual blast furnace production process, improving the prediction accuracy of the GUR efficiently.
This paper proposes an inverse compensation feed-forward control strategy for a vertical pneumatic artificial muscle (PAM) system. Firstly, we conduct a preliminary experiment on the vertical PAM system, and on this b...
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This paper proposes an inverse compensation feed-forward control strategy for a vertical pneumatic artificial muscle (PAM) system. Firstly, we conduct a preliminary experiment on the vertical PAM system, and on this basis, we analyze the motion characteristics of the system. Moreover, we clarify the control objective of this paper. Then, we establish a model that can describe the hysteresis characteristics of the system, and we further construct an inverse compensation feedforward controller by inversing this established model. Finally, we carry out some tracking control experiments based on the vertical PAM experimental platform to verify the effectiveness and superiority of the proposed control strategy,
Due to the rapid growth of online education worldwide, assessing the learning effectiveness of students during online classes has become increasingly challenging for teachers. In this paper, a method of assessing onli...
Due to the rapid growth of online education worldwide, assessing the learning effectiveness of students during online classes has become increasingly challenging for teachers. In this paper, a method of assessing online education effect based on YOLOv8 and Vision Transformer is proposed. Firstly, the drowsiness state of students in an online teaching unconstraint environment is estimated by using YOLOv8, and then the gaze direction of awake students is estimated by using Vision Transformer to assess the students' attention levels during online education. The results from YOLOv8 are determined based on the calculated probabilities of drowsiness or wakefulness. And then gaze estimation method proposed in this paper was compared with state-of-the-art methods on the MPIIFaceGaze and Gaze360 datasets in which the angular errors of gaze estimation are 4.58° and 12.27°, respectively. We conducted experiments and analysis on a self-made dataset, from which the results demonstrate the feasibility of our method in an unconstrained environment.
This paper present a feedback linearization technique for affine nonlinear systems that is independent of system dynamics. First, a input-output feedback linearization correction framework is described, and a interfer...
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This paper present a feedback linearization technique for affine nonlinear systems that is independent of system dynamics. First, a input-output feedback linearization correction framework is described, and a interference estimator is employed to guarantee the stability of plant during the learning process. Then, a model-free Q-learning algorithm is presented to solve the feedback linearized controller. Finally, the position control of a single-link flexible joint manipulator system is used as an example to demonstrate the effectiveness of the method.
In this paper, the preassigned-time synchronization (PTS) problem for a fifth-order memristive chaotic circuit (MCC) is investigated by designing a time-dependent intermittent controller. First, the dynamic characteri...
In this paper, the preassigned-time synchronization (PTS) problem for a fifth-order memristive chaotic circuit (MCC) is investigated by designing a time-dependent intermittent controller. First, the dynamic characteristics of the MCC, especially the existence and occurrence of chaos, are investigated by simulation experiments. Besides, the stability of the equilibrium points is discussed by using Routh-Hurwitz criterion. Then, a time-dependent intermittent controller is designed and the PTS of MCC is realized via the presented controller. Finally, the effectiveness of theoretical results is verified by means of numerical simulations.
Prompt detection of bit bounce can prevent serious incidents and is of great importance for safe and efficient deep geological drilling. In the early stage of bit bounce, signal changes are relatively weak. In additio...
Prompt detection of bit bounce can prevent serious incidents and is of great importance for safe and efficient deep geological drilling. In the early stage of bit bounce, signal changes are relatively weak. In addition, there are differences in the topological relationships of samples at different time instances in normal state and bit bounce. These factors present a challenge to timely and accurate bit bounce detection. Therefore, this paper proposes a bit bounce detection method based on multi-feature graph and graph convolution networks. A multi-feature graph construction method using process variables, mean value, Mahalanobis distance, and Euclidean distance is proposed, and a two-layer graph convolutional network is designed to realize deep feature extraction and incident detection. The effectiveness and superiority of the proposed method are demonstrated by a real drilling industrial case.
It is always a challenging task to service sudden events in non-convex and uncertain environments, and multi-agent coverage control provides a powerful theoretical framework to investigate the deployment problem of mo...
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This paper studies the finite-time tracking control problem for the stochastic drill-bits system driven by a Lévy process with the bit-rock interaction. The finite-time tracking control problem of the stochastic ...
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This paper studies the finite-time tracking control problem for the stochastic drill-bits system driven by a Lévy process with the bit-rock interaction. The finite-time tracking control problem of the stochastic drill-bits system driven by a Lévy process can be regarded as the finite-time stability analysis for the stochastic nonlinear equations driven by a Lévy process. So the Lyapunov-type finite-time stability theorem is firstly developed to obtain the finite-time almost sure stability for n-dimensional stochastic nonlinear equations driven by a Lévy process. Then based on finite-time stability theorem, the adaptive finite-time almost sure tracking of drill-b its is achieved. A drill-bit simulation is given to demonstrate the control effect.
This article proposes a distributed secondary control strategy for accurate current allocation and voltage restoration in DC microgrids. This method consists of a high coefficient droop controller and a voltage shifti...
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This article proposes a distributed secondary control strategy for accurate current allocation and voltage restoration in DC microgrids. This method consists of a high coefficient droop controller and a voltage shifting controller which needs to obtain the voltage information of the adjacent converters through a low bandwidth communication link, and then calculates the voltage shifting required for the reference voltage. The system small-signal model considering the specific converter object is established to analyze the regulation rules of the parameters of the secondary controller. Moreover, the proposed method does not require complexcontrol structure and a large amount of information of converter variables. A DC microgrid environment was built in MATLAB/Simulink, and the effectiveness of the proposed control strategy was verified.
In this paper, based on the sliding-mode control, the finite-time synchronization of delayed competitive neural networks with external disturbances is investigated. Firstly, a controller and two sliding-mode surfaces ...
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In this paper, based on the sliding-mode control, the finite-time synchronization of delayed competitive neural networks with external disturbances is investigated. Firstly, a controller and two sliding-mode surfaces are designed. Then, by utilizing the finite-time stability theory, the error states of drive and response delayed competitive neural networks are able to reach the designed surfaces in a finite time and then keep on the surfaces, where the states of equivalent system will approach zero in a finite time. Finally, a numerical example is presented to illustrate the effectiveness of the theoretical results.
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