The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning co...The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.展开更多
Automation Gauge Control(AGC) and Automatic Shape Control(ASC) are coupling each other. The coupling models of AGC-ASC synthetic system for the thickness-crown have been established and two artificial neural networks ...Automation Gauge Control(AGC) and Automatic Shape Control(ASC) are coupling each other. The coupling models of AGC-ASC synthetic system for the thickness-crown have been established and two artificial neural networks controllers are given. The simulation of computer shows that the AGC-ASC synthetic system can obtain the expected thickness and shape precision with both schemes.展开更多
In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system (MEMS) gyroscope are analyzed in principle. A novel drive circuit for...In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system (MEMS) gyroscope are analyzed in principle. A novel drive circuit for the MEMS gyroscope in digital closed-loop control is proposed, which utilizes a digital phase-locked loop (PLL) in frequency control and an automatic gain control (AGC) method in amplitude control. A digital processing circuit with a field programmable gate array (FPGA) is designed and the experiments are carried out. The results indicate that when the temperature changes, the drive frequency can automatically track the resonant frequency of gyroscope in drive mode and that of the oscillating amplitude holds at a set value. And at room temperature, the relative deviation of the drive frequency is 0.624 ×10^-6 and the oscillating amplitude is 8.0 ×10^-6, which are 0. 094% and 18. 39% of the analog control program, respectively. Therefore, the control solution of the digital PLL in frequency and the AGC in amplitude is feasible.展开更多
Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system ...Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.展开更多
Since wind power has the features of being intermittent and unpredictable, and usually needs transmission over long distances, grid integration of large-scale wind power will exert signif icant influence on power grid...Since wind power has the features of being intermittent and unpredictable, and usually needs transmission over long distances, grid integration of large-scale wind power will exert signif icant influence on power grid planning and construction, and will make a heavy impact on the safe and reliable operation of power systems. To deal with the diff iculties of large scale wind power dispatch, this paper presents a new automatic generation control (AGC) scheme that involves the participation of wind farms. The scheme is based on ultra-short-term wind power forecast. The author establishes a generation output distribution optimization mode for the power system with wind farms and verif ies the feasibility of the scheme by an example.展开更多
The coupling models for the thickness-crown objects is established. A Dynamic Matrix Controller based on the TH neural networks is given with the convergence property. The computer simulations with the AGC-ASC decoupl...The coupling models for the thickness-crown objects is established. A Dynamic Matrix Controller based on the TH neural networks is given with the convergence property. The computer simulations with the AGC-ASC decoupled neural networks predictive control system is complemented and it shows that the stable states of neural networks are reached with on more that one μs, this has not only sahsfied the fast property of rolling process, but also obtained a higher control index.展开更多
针对AGC控制中火电机组响应时滞长、机组爬坡速率低的问题,提出了一种基于模糊控制策略的电池储能系统(Battery Energy Storage System,BESS)辅助AGC调频方法。该方法以区域控制偏差(Area Control Error,ACE)及其变化率作为模糊控制器...针对AGC控制中火电机组响应时滞长、机组爬坡速率低的问题,提出了一种基于模糊控制策略的电池储能系统(Battery Energy Storage System,BESS)辅助AGC调频方法。该方法以区域控制偏差(Area Control Error,ACE)及其变化率作为模糊控制器的输入量,BESS的参考功率变化量作为输出量,根据系统的运行状态调节BESS输出功率,辅助火电机组改善电网的动态调频性能。基于Matlab/Simulink平台的仿真结果表明,BESS能够迅速响应负荷扰动,减小了系统频率偏差和联络线功率偏差,降低了系统的超调作用,有助于提高电网AGC调频能力和增强系统的稳定性。展开更多
基金Project(51074051)supported by the National Natural Science Foundation of China
文摘The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.
文摘Automation Gauge Control(AGC) and Automatic Shape Control(ASC) are coupling each other. The coupling models of AGC-ASC synthetic system for the thickness-crown have been established and two artificial neural networks controllers are given. The simulation of computer shows that the AGC-ASC synthetic system can obtain the expected thickness and shape precision with both schemes.
基金The National Natural Science Foundation of China(No. 60974116 )the Research Fund of Aeronautics Science (No.20090869007)Specialized Research Fund for the Doctoral Program of Higher Education (No. 200902861063)
文摘In order to effectively control the working state of the gyroscope in drive mode, the drive characteristics of the micro electromechanical system (MEMS) gyroscope are analyzed in principle. A novel drive circuit for the MEMS gyroscope in digital closed-loop control is proposed, which utilizes a digital phase-locked loop (PLL) in frequency control and an automatic gain control (AGC) method in amplitude control. A digital processing circuit with a field programmable gate array (FPGA) is designed and the experiments are carried out. The results indicate that when the temperature changes, the drive frequency can automatically track the resonant frequency of gyroscope in drive mode and that of the oscillating amplitude holds at a set value. And at room temperature, the relative deviation of the drive frequency is 0.624 ×10^-6 and the oscillating amplitude is 8.0 ×10^-6, which are 0. 094% and 18. 39% of the analog control program, respectively. Therefore, the control solution of the digital PLL in frequency and the AGC in amplitude is feasible.
文摘Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control,automatic generation control(AGC) plays a crucial role. In this paper, multi-area(Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative(PID) controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm(FFA). The experimental results demonstrated the comparison of the proposed system performance(FFA-PID)with optimized PID controller based genetic algorithm(GAPID) and particle swarm optimization(PSO) technique(PSOPID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error(ITAE) cost function with one percent step load perturbation(1 % SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.
基金supported by National Natural Science Foundation of China(61100159,61233007,61503371)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology,and Innovation of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid,Energy Management System for Micro-smart Grid
文摘Since wind power has the features of being intermittent and unpredictable, and usually needs transmission over long distances, grid integration of large-scale wind power will exert signif icant influence on power grid planning and construction, and will make a heavy impact on the safe and reliable operation of power systems. To deal with the diff iculties of large scale wind power dispatch, this paper presents a new automatic generation control (AGC) scheme that involves the participation of wind farms. The scheme is based on ultra-short-term wind power forecast. The author establishes a generation output distribution optimization mode for the power system with wind farms and verif ies the feasibility of the scheme by an example.
文摘The coupling models for the thickness-crown objects is established. A Dynamic Matrix Controller based on the TH neural networks is given with the convergence property. The computer simulations with the AGC-ASC decoupled neural networks predictive control system is complemented and it shows that the stable states of neural networks are reached with on more that one μs, this has not only sahsfied the fast property of rolling process, but also obtained a higher control index.
文摘针对AGC控制中火电机组响应时滞长、机组爬坡速率低的问题,提出了一种基于模糊控制策略的电池储能系统(Battery Energy Storage System,BESS)辅助AGC调频方法。该方法以区域控制偏差(Area Control Error,ACE)及其变化率作为模糊控制器的输入量,BESS的参考功率变化量作为输出量,根据系统的运行状态调节BESS输出功率,辅助火电机组改善电网的动态调频性能。基于Matlab/Simulink平台的仿真结果表明,BESS能够迅速响应负荷扰动,减小了系统频率偏差和联络线功率偏差,降低了系统的超调作用,有助于提高电网AGC调频能力和增强系统的稳定性。