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Journal of Control Science and Engineering publishes research investigating the design, simulation and modelling, implementation, and analysis of methods and technologies for control systems and applications.
Chief Editor, Professor Seiichiro Katsura, is based at Keio University, Japan. His laboratory is developing a novel synthesis method based on the infinite-order modeling and energy conversion of electromechanical integration systems.
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Modified Passivity-Based Control for LCL-Filtered Grid-Tied Inverter with Output Admittance Reshaping
As a nonlinear control method, the Euler–Lagrange- (EL-) based passivity-based control (PBC) has been studied for grid-tied converters based on energy function to achieve better performance. However, the EL-based PBC method is dependent on an accurate mathematical model. In the traditional EL-based PBC research for LCL-filtered grid-tied inverter, the effect of the digital control delay is rarely considered and the stability under the grid impedance uncertainties is not discussed, especially in the capacitive grid or complex weak grid. To address these concerns, this study proposes a modified EL-based PBC method based on the output admittance reshaping for LCL-filtered grid-tied inverters. The system’ passive region is expanded by adding capacitor current feedback loop up to the Nyquist frequency. The potential resonance is thus eliminated irrespective of the grid impedance. Additionally, the stable region and control parameters design methods of the modified EL-based PBC method with inverter-side control are also carried out. To verify the correctness of the theoretical analysis, both simulation and experimental results are investigated from a 3 kW grid-tied inverter prototype.
Intermittent Control for Synchronization of Discrete-Delayed Complex Cyber-Physical Networks under Mixed Attacks
This paper is concerned with the synchronization control problem for discrete-delayed complex cyber-physical networks under mixed attacks. To handle input delays and mixed attacks, the intermittent control mechanism is employed, which is distinctly different from the traditional control method. By utilizing the Lyapunov stability theorem, a novel synchronization control method is developed for the synchronization control of complex cyber-physical networks with mixed attacks. Then, sufficient conditions are derived to guarantee that the synchronization error dynamics are ultimately bounded. Moreover, the conditions for a special case where the absence of input delays. Subsequently, certain optimization problems are formulated with the aim to minimize the synchronization error. Finally, two numerical examples are given to verify the effectiveness and superiority of the proposed synchronization control strategy.
On the Effectiveness of Graph Statistics of Shareholder Relation Network in Predicting Bond Default Risk
Starting from the theoretical effectiveness of shareholder relation network information for predicting bond default risk, we propose two efficient schemes for extracting two different graph statistics of shareholder relation networks: graph structure statistics and graph distance statistics. In order to test the effectiveness of the two schemes, seven machine learning methods and three types of prediction tasks are used. The shareholder relation network information’s effectiveness and machine learning methods are also analyzed. Results show that the graph statistics of shareholder relationship networks are insufficient to be used independently as input features for predicting bond default risk but can provide helpful incremental information based on financial features. The shareholder relation information is effective for predicting bond default risk. The structure statistics perform best among all graph statistics overall, and Cascade Forest and LightGBM perform best among all seven machine learning methods.
Coordinated Compliance Control Method of Five-Axis Redundant Industrial Manipulator Based on Monocular Vision
In order to improve the accuracy of the five-axis redundant industrial robot arm in grasping static objects and shorten the grasping time, a coordinated compliance control method based on a monocular vision for the five-axis redundant industrial robot arm is proposed in this paper. Using the monocular vision ranging method, the three-dimensional coordinates of the target object in a base coordinate system of the five-axis redundant industrial robotic arm are calculated and object target positioning is achieved. According to the acquired object target position, the traditional Euler angle is used to calculate the actuator posture impedance at the end of the robotic arm, thereby realizing the coordinated compliant control of the five-axis redundant industrial manipulator. The simulation experiment results show that the proposed coordinated compliance control method for a five-axis redundant industrial manipulator based on monocular vision can successfully grasp the target object in the shortest time and has high practical value.
Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
In order to solve the problem that the existing LoRaWAN adaptive data rate control algorithm leads to low data transmission efficiency in the case of network congestion, a method combining a fuzzy logistic regression classifier and an improved adaptive data rate controller adjusting the avoidance time was proposed. The classifier could obtain the predicted congestion state by logistic regression learning. The data rate controller determined the data rate adjustment scheme according to the predicted congestion state. The experimental results showed that when the network congestion occurred in about 12s, the number of packet loss by the LoRaWAN default method was higher than that by the method in the research. The value of ADR_ MSG_CNT of the 15 source nodes in the method was 30 within 0–10 s, while the RCV_ACK_CNT of some nodes was 0. It proved that the method was more efficient than the original LoRaWAN adaptive data rate control algorithm.
Analysis and Control of Abnormal Vibration of End Wall on High-Speed Electric Multiple Units
In view of the abnormal vibration of the body end wall during the high-speed operation of electric multiple units (referred hereafter as EMU), the vibration and noise characteristics of the body end wall area are analyzed through the line test. Combined with the end wall modal simulation results, the generation mechanism of the abnormal vibration of the body end wall is analyzed. The results show that when the train is running at a high speed, the aerodynamic excitation of the windshield cavity outside the body end wall acts on the end wall, arousing the first-order bending natural frequency of the body end wall, resulting in resonance of the body end wall, and then causing abnormal vibration and noise in the body end wall area. In order to solve this problem, installing a deflector (guiding plate) above the windshield in the vehicle body end wall area can effectively suppress the aerodynamic excitation acting on the vehicle body end wall. After optimization, the abnormal vibration and noise in the vehicle body end wall area are significantly reduced. The corresponding peak value at 40 Hz of the vehicle body end wall vibration spectrum is reduced by 85%, and the peak noise is reduced by 12%, The correctness of the mechanism analysis of abnormal vibration in the headwall area is verified, which provides a reference basis for guiding the structural optimization and operation and maintenance of rail vehicles.