Advanced Control for Applications最新文献

Aiming at large system operation fluctuations caused by the technical control of virtual synchronous generators, this article studies the introduction of interface converter control power, builds a virtual synchronous generator (VSG)-based hybrid microgrid model and adaptive control strategy. Finally it optimizes it with fuzzy logic to obtain an fuzzy logic controller (FLC) based adaptive VSG control strategy. The experimental results show that under the FLC-based adaptive VSG control strategy, in the reverse current mode, the system regression time is 0.37 s, and the DC bus voltage is 6.5 V; In the rectification mode, the system regression time is 0.49 s, and the DC bus voltage is 2.1 V. The results obtained are faster than the traditional VSG control strategy, and the DC bus voltage is 42.48%–68.66% lower. In summary, the suggested control approach is effective and reliable under the two operation modes, which can make the system operate safely and stably.

In the process of grid connection of irregular output micro-grid systems, it is of great research significance to make micro-grid scheduling operate more effectively and economically. To minimize the environmental and total operating costs of the micro-grid intelligent scheduling system during grid connection, this study proposes a micro-grid intelligent scheduling model based on an optimized particle swarm optimization algorithm. The optimized particle swarm algorithm mainly improves the problem of the particle swarm algorithm being prone to local optima, making it reduce the possibility of local convergence. Comparative tests were conducted on the improved IPSO algorithm, and the results showed that the non-dominated solution concentration pollution emissions obtained by the improved IPSO algorithm were at least 18326 Ib, which was lower than the comparison algorithm. In the empirical analysis of the intelligent scheduling model based on the improved IPSO algorithm, the convergence and satisfaction of the model were 0.0054 and 0.922, respectively, which were superior to the comparison algorithm. The above results indicate that the intelligent scheduling model for micro-grid based on the improved IPSO algorithm has good economy and stability. Compared with traditional energy dispatch methods, this energy dispatch mode has higher economic benefits and is of great significance for promoting the development of micro-grid.

In the control system of permanent magnet synchronous motor, in order to improve real-time performance and computational complexity, a new method of implementing segmented current control of permanent magnet motor using duty cycle modulation is proposed. The term plane is divided into three sectors through three-phase voltage vector, and current prediction iteration is performed to obtain the relevant duty cycle, and the periodic modulation of this method (DM-MPCC) is verified by experiments and the traditional DV-MPCC (DV-MPCC), the method is repeated more than 150 times, the time required for this method is 2.863 s, saving 52.073% of the computing time, while the modulation duty of DM-MPCC It is also more stable than the waveform, and the current THD = 2.986% DM-MPCC is much lower than the conventional method. DM-MPCC has less pulsation on the dq axis at full speed than DV-MPCC. The results show that the method has a faster operation speed and better real-time performance, which shows the superiority of this method in practical applications.

In this article, we propose a double reconfigurable intelligent surface (RIS)-aided ambient backscatter communication (AmBC) network combined with non-orthogonal multiple access (NOMA) technology, which not only successfully assists the base station (BS) in connecting with the cell edge user, but also enhances backscatter communication rate, energy efficiency, and spectrum efficiency. In an effort to obtain the highest backscatter communication rate, we design a RIS and BS-based resource allocation problem which is solved by determining the optimal phase shifts of RISs and the optimal power allocation for signals of NOMA users. We break it down into two smaller challenges in order to discover the best solution. For one thing, we iterate the optimal phase shifts between the two RIS combinations using an alternating optimization technique. For another, the bisection method is used to provide the NOMA user with the ideal power allocation. Finally, the results of the simulation substantiate the viability of the proposed scheme.

The fault detection with a single sensor cannot comprehensively use the multi-sensor correlation information of underwater thruster. To solve the issue that in the case of entanglement, a kind of fault diagnosis method of underwater thruster based on the combination of current and rotational speed signal correlation analysis and support vector machine is proposed. Firstly, the collected current and speed signals of underwater thrusters under different states are normalized, the variable sampling data points is adopted to refine the time of fault occurrence; Secondly, the cross correlation and autocorrelation coefficients of normalized current and speed signals are calculated based the variable sampling data points number and the correlation matrix is formed at different sampling time based on the cross correlation and autocorrelation coefficients. Finally, the support vector machine was applied to diagnose whether or not the fault produces and the time of fault occurrence with the correlation coefficients sequence. To verify the effectiveness of the proposed method, the fault simulation platform and data acquisition software are designed, the fault data in the case of thruster with entanglement are collected in time to test the proposed method. The results show that compared with the fault diagnosis method using only one speed or current signal, the proposed analytical method based on the correlation coefficients can fully extract the correlation information of underwater thruster fault, and the time extraction of fault occurrence is more sufficient, effectively improving the accuracy of underwater thruster fault diagnosis.

In recent years, the development of high-speed railways in China has been rapid. High-speed railway bridges play an essential role whenever the railway intersects with existing facilities in three dimensions. With the increasing speed of high-speed railways and increasingly complex geographical locations, the span of bridges is constantly increasing. Based on their advantages, steel structures in large-span bridges are beginning to replace traditional concrete structures. Taking the steel cover beam technology applied in the Fuqiangbao Tremendous Bridge as a starting point, this paper uses Rhino parameterized modeling and Abaqus software to conduct finite element analysis on the stress of steel cover beams. It compares and analyzes stress under different conditions. The results show that the steel cover beam's most unfavorable and unstable position in this paper is at the support on the stress side. This provides a reference for monitoring the steel cover beam after its application in the Fuqiangbao Tremendous Bridge and technical accumulation for the application of steel cover beam technology.

As a renewable and clean energy source, wind energy can be converted into electricity by wind turbines. Currently, it is challenging to suppress the edgewise vibration of the wind turbine blades to improve the efficiency and service life of wind turbines. In this paper, active disturbance rejection control (ADRC)is applied to vibration suppression at the blade edge of wind turbines. First, the proposed system is mathematically modeled and analyzed in the frequency domain. Second, the ADRC is designed for the proposed system. Then, time domain analysis, frequency domain analysis, and uncertainty analysis of the closed-loop system were carried out. It has been shown that the proposed controller has 12.2% less overshoot and 55.8% less setting time when subjected to perturbations than the PID controller. And the proposed controller has 33.9% less overshoot and 55.9% less setting time when subjected to perturbations than the SMC. Furthermore, the resonance frequency range of the proposed controller has been effectively reduced, and the peak resonance has been reduced by 41.7%. This reflects that the ADRC has a significant vibration suppression effect on blade edgewise vibrations compared with PID controllers and SMC.

Although the smart microgrid improves the power quality of the power system, it still has some security risks. So, this paper proposes a network security risk detection method of an intelligent microgrid monitoring system based on the artificial immune algorithm. By analyzing the structure of a smart microgrid monitoring system and introducing Policy Protection Detection Response (P2DR) dynamic network security model and ale static network security analysis method, the network security risk of the microgrid monitoring system is evaluated. The theoretical model is analyzed by the overall framework of the artificial immune algorithm, and its term definition is given. The mutation self is detected by self-dynamic description and immune cell evolution process with the network structure brought into and the risk of the computing network facing different attack subjects is analyzed. This method has a high detection accuracy for more than 10 kinds of network attack modes, the highest detection accuracy is 98%, and the average time is only 0.8 s. Compared with other methods, this method has higher detection accuracy and faster detection speed. It is universal in various network attack modes and can detect the possible network security risks of the intelligent microgrid monitoring system and protect its safe and stable operation.

The control problem of the rotary double inverted pendulum (double Furuta pendulum) is nontrivial because of underactuation and strong nonlinearities in the associated state-space model. The system has three degrees of freedom (one actuated and two unactuated joints) while receiving only one control input. In this article, a novel nonlinear optimal (H-infinity) control approach is developed for the dynamic model of the rotary double inverted pendulum. First, the dynamic model of the double pendulum undergoes approximate linearization with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. The linearization process takes place at each sampling instance around a temporary operating point which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector. At a next stage a stabilizing H-infinity feedback controller is designed. To compute the controller's feedback gains an algebraic Riccati equation has to be solved at each time-step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. To implement state estimation-based control without the need to measure the entire state vector of the rotary double-pendulum the H-infinity Kalman filter is used as a robust state observer. The nonlinear optimal control method achieves fast and accurate tracking of setpoints by all state variables of the rotary double inverted pendulum under moderate variations of the control input.