This paper presents an improved stability criterion and controller design scheme condition for a networked control system under denial of service(DoS) attack. Firstly, the DoS attack interval is divided into attack in...
This paper presents an improved stability criterion and controller design scheme condition for a networked control system under denial of service(DoS) attack. Firstly, the DoS attack interval is divided into attack interval and no attack interval, therefore, a switching-like event-triggered control can be established to reduce the waste of network resources and improve network efficiency. Then, the studied system is transformed into a time-delay system, and an improved stability criterion and controller design method are established by using Lyapunov-Krasovskii functional(LKF). Finally, the effectiveness of the proposed method is verified by a simulation example.
This paper uses the wave equation to explain the torsional motion of the drill-string system.S olving the wave equation with the D'Alembert method,a neutral time-delay model of the drill-string system is *** distu...
This paper uses the wave equation to explain the torsional motion of the drill-string system.S olving the wave equation with the D'Alembert method,a neutral time-delay model of the drill-string system is *** disturbance input,caused by the bit-rock interaction,is given consideration,and an equivalent-input-disturbance(EID) based controller is designed to mitigate the disturbance in the established *** the actual drilling procedure,the system input time-delay increases as the length of the drill columns *** the influence of system input time-delay in the drilling procedure is ignored,it will most likely lead to the drill-string system instability and cause serious *** essential contribution of this paper is the incorporation of input time-delay into the EID based control *** the system's input time-delay,the proposed model is more practical and has significant implications for stick-slip vibration assessment and control in drilling procedures.
Geo-hazards have become one of the main disasters endangering the safety of people's lives and property in the *** order to improve the early warning of disasters, a persistent monitoring method of multi-agent sys...
Geo-hazards have become one of the main disasters endangering the safety of people's lives and property in the *** order to improve the early warning of disasters, a persistent monitoring method of multi-agent systems is proposed in this *** ensure that the agent's energy is never exhausted, the set invariance constraint is included in the optimization problem. The goal is to minimize the difference between the actual control input of the robot and the nominal control input corresponding to the task to be performed. Moreover, the control barrier function(CBF) is used to transform the forward invariance of a subset of the robot state space into a control input constraint. The coverage control method in an uncertain environment is verified by numerical simulation. This work provides new insights into effective monitoring and early warning of geo-hazards.
In this paper, the H∞ consensus control problem for Markov jump multi-agent systems with imperfect time-varying transition probabilities is studied. Both the transition probability matrix and the higher-level transit...
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Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller ...
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Geological exploration is essential for economic and social progress, with lithology identification being a key technology that improves exploration precision and resource development efficiency. This paper presents a...
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ISBN:
(数字)9798350368604
ISBN:
(纸本)9798350368611
Geological exploration is essential for economic and social progress, with lithology identification being a key technology that improves exploration precision and resource development efficiency. This paper presents a real-time identification method of formation lithology in drilling process based on pre-training language model, which is divided into three stages. In this first stage, the drilling data undergoes rigorous cleaning, feature selection, and normalization to eliminate noise and anomalies. In the second stage, key model inputs such as weight on bit (WOB), rate of penetration (ROP), rotation speed (RPM), torque, and pump volume (P) are identified through detailed drilling mechanism analysis. In the last stage, a real-time identification method of formation lithology in drilling process based on pre-training language model is proposed, which realizes high-precision real-time identification in drilling process. The effectiveness of the proposed method is proved by comparison with common methods.
The multitude of advantages offered by distributed power generation units are recognized as crucial factors in enhancing the security of distribution networks. Ensuring the optimal size and placement of distributed ge...
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ISBN:
(数字)9798350367690
ISBN:
(纸本)9798350367706
The multitude of advantages offered by distributed power generation units are recognized as crucial factors in enhancing the security of distribution networks. Ensuring the optimal size and placement of distributed generation (DG) units not only enhances system security but also increases profitability. Haphazard placement of DG units may lead to adverse impacts on the power system, resulting in increased power losses and diminished voltage distribution. Therefore, to ensure the optimal size and placement of DG units, this paper proposes a method to optimize DG scheduling and operation, thereby improving voltage distribution, reducing power losses, and enhancing the overall reliability of the entire grid. To reduce power loss (PL) and improve voltage distribution (VP), an adaptive chaotic particle swarm optimization (ACPSO) algorithm is employed to determine the optimal locations and sizes of DG units. By comparing this algorithm with traditional approaches, its efficacy in enhancing performance can be discerned.
Pairwise similarity has been widely used for image classification by propagating the class information from labeled images to unlabeled images and predicting the classes of unlabeled images accordingly. Although widel...
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In this paper, the problem of event-based fault-tolerant model predictive load frequency control is investigated for the power system where the electrolytic aluminum load participates in frequency modulation and actua...
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ISBN:
(数字)9798350373691
ISBN:
(纸本)9798350373707
In this paper, the problem of event-based fault-tolerant model predictive load frequency control is investigated for the power system where the electrolytic aluminum load participates in frequency modulation and actuator faults. A dynamic event-triggered mechanism containing an internal dynamic variable (IDV) and an adjustable variable is designed to reduce the data transmission burden. The fault-tolerant model predictive control (FTMPC) problem is expressed as a "min-max" optimization problem (OP). According to the Lyapunov-like function that depends on the IDV, an auxiliary OP with constrained linear matrix inequalities is constructed. By solving the auxiliary OP, the FTMPC controller gains that ensure the input-to-state stability of the closed-loop system can be obtained. The effectiveness of the proposed algorithm is verified through a simulation example.
One of the key concerns in today's steel business is how to effectively save energy and reduce emissions, since the concepts of green environmental preservation, energy conservation, and emission reduction are dee...
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ISBN:
(数字)9789887581598
ISBN:
(纸本)9798331540845
One of the key concerns in today's steel business is how to effectively save energy and reduce emissions, since the concepts of green environmental preservation, energy conservation, and emission reduction are deeply ingrained in people's hearts. Fuel ratio is a key parameter in blast furnace steelmaking. Identifying the factors that influence the fuel ratio and being able to model and predict it can greatly help in guiding the stable operation of the blast furnace, reducing fuel ratio, saving energy, and cutting emissions. In this paper, the fuel ratio mechanism of blast furnace is analyzed, and the parameters affecting the fuel ratio are initially selected. Subsequently, the parameters with the highest correlation to the fuel ratio are identified using the maximum correlation coefficient method. A CNN-LSTM-Attention-based fuel ratio prediction model was developed, and its accuracy and efficacy were demonstrated through comparison with three other models.
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