采用传统频域方法进行发电机比例–积分–微分(proportional integral differential,PID)励磁调节器的参数设计时只考虑本机组的运行,而忽视了电网的整体运行情况,且性能好坏取决于设计人员的经验。针对这种情况,提出了基于大型电力系...采用传统频域方法进行发电机比例–积分–微分(proportional integral differential,PID)励磁调节器的参数设计时只考虑本机组的运行,而忽视了电网的整体运行情况,且性能好坏取决于设计人员的经验。针对这种情况,提出了基于大型电力系统时域仿真曲线的励磁PID调节器闭环优化方法,既能综合考虑机组和电网的运行情况,又能克服传统设计过于依赖经验的不足。该方法使用时域积分性能指标来评价含有PID调节器的闭环电力系统的综合性能,运用Nelder-Mead单纯形方法来有效搜索最优的PID参数。在实际大型电网中的应用结果表明,该优化方法可有效提高大电网电压的动态调节能力,有很好的实际应用前景。展开更多
提出了种应用于飞轮储能系统的神经元自适应比例?积分?微分(proportional integral differential,PID)控制算法。该算法基于传统的双闭环调速系统与神经网络理论,实现对飞轮驱动电机的控制,使飞轮驱动电机能够根据系统要求,驱动飞轮储...提出了种应用于飞轮储能系统的神经元自适应比例?积分?微分(proportional integral differential,PID)控制算法。该算法基于传统的双闭环调速系统与神经网络理论,实现对飞轮驱动电机的控制,使飞轮驱动电机能够根据系统要求,驱动飞轮储能单元储存或释放能量。运用李亚普诺夫稳定性理论证明了该控制算法的稳定性和有效性,并给出了其稳定性条件。经过仿真验证,该算法可以有效地实现对飞轮储能单元的充放电控制,其控制参数可以随着系统的运行自适应调节,飞轮储能单元的控制精度和鲁棒性也有所提高。展开更多
为实现多变风况下直驱永磁风力发电系统的稳定、高效运行,提出一种模型预测电流控制MPCC(model predictive current control)与分数阶比例-积分-微分PIγDμ(fractional-order proportional-integral-derivative)相结合的策略。首先,利...为实现多变风况下直驱永磁风力发电系统的稳定、高效运行,提出一种模型预测电流控制MPCC(model predictive current control)与分数阶比例-积分-微分PIγDμ(fractional-order proportional-integral-derivative)相结合的策略。首先,利用MPCC两步预测法建立风力发电机组的电流预测模型,得到不同控制集下的电流预测值,评估确定出满足代价函数最小所对应的最优电流预测值。然后,设计PIγDμ控制器,将最优电流预测值和参考电流作为输入参数,经PIγDμ控制器输出得到最优控制电压矢量,实现对系统进行控制。最后,建立仿真模型,与双闭环PI和传统MPCC控制策略进行对比,验证所提控制策略的有效性和优越性。展开更多
Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototyp...Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver's seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.展开更多
文摘采用传统频域方法进行发电机比例–积分–微分(proportional integral differential,PID)励磁调节器的参数设计时只考虑本机组的运行,而忽视了电网的整体运行情况,且性能好坏取决于设计人员的经验。针对这种情况,提出了基于大型电力系统时域仿真曲线的励磁PID调节器闭环优化方法,既能综合考虑机组和电网的运行情况,又能克服传统设计过于依赖经验的不足。该方法使用时域积分性能指标来评价含有PID调节器的闭环电力系统的综合性能,运用Nelder-Mead单纯形方法来有效搜索最优的PID参数。在实际大型电网中的应用结果表明,该优化方法可有效提高大电网电压的动态调节能力,有很好的实际应用前景。
文摘提出了种应用于飞轮储能系统的神经元自适应比例?积分?微分(proportional integral differential,PID)控制算法。该算法基于传统的双闭环调速系统与神经网络理论,实现对飞轮驱动电机的控制,使飞轮驱动电机能够根据系统要求,驱动飞轮储能单元储存或释放能量。运用李亚普诺夫稳定性理论证明了该控制算法的稳定性和有效性,并给出了其稳定性条件。经过仿真验证,该算法可以有效地实现对飞轮储能单元的充放电控制,其控制参数可以随着系统的运行自适应调节,飞轮储能单元的控制精度和鲁棒性也有所提高。
文摘为实现多变风况下直驱永磁风力发电系统的稳定、高效运行,提出一种模型预测电流控制MPCC(model predictive current control)与分数阶比例-积分-微分PIγDμ(fractional-order proportional-integral-derivative)相结合的策略。首先,利用MPCC两步预测法建立风力发电机组的电流预测模型,得到不同控制集下的电流预测值,评估确定出满足代价函数最小所对应的最优电流预测值。然后,设计PIγDμ控制器,将最优电流预测值和参考电流作为输入参数,经PIγDμ控制器输出得到最优控制电压矢量,实现对系统进行控制。最后,建立仿真模型,与双闭环PI和传统MPCC控制策略进行对比,验证所提控制策略的有效性和优越性。
基金Projects(51078087, 51178158) supported by the National Natural Science Foundation of ChinaProject(11040606Q39) supported by the Natural Science Foundation of Anhui Province, ChinaProjects(2012HGQC0015, 2011HGBZ0945) supported by the Fundamental Research Funds for the Central Universities
文摘Two simple and effective control strategies for a multi-axle heavy truck, modified skyhook damping (MSD) control and proportional-integration-derivative (PID) control, were implemented into functional virtual prototype (FVP) model and compared in terms of road friendliness and ride comfort. A four-axle heavy truck-road coupling system model was established using FVP technology and validated through a ride comfort test. Then appropriate passive air suspensions were chosen to replace the rear tandem suspensions of the original truck model for preliminary optimization. The mechanical properties and time lag of dampers were taken into account in simulations of MSD and PID semi-active dampers implemented using MATLAB/Simulink. Through co-simulations with Adams and MATLAB, the effects of semi-active MSD and PID control were analyzed and compared, and control parameters which afforded the best comprehensive performance for each control strategy were chosen. Simulation results indicate that compared with the passive air suspension truck, semi-active MSD control improves both ride comfort and road-friendliness markedly, with optimization ratios of RMS vertical acceleration and RMS tyre force ranging from 10.1% to 44.8%. However, semi-active PID control only reduces vertical vibration of the driver's seat by 11.1%, 11.1% and 10.9% on A, B and C level roads respectively. Both strategies are robust to the variation of road level.
