The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and...The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and power stations from stockpiles.BWRs are very large in size,heavy in weight,expensive in price,and slow in motion.There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction,turbulent wind,its own dynamics,and encoder limitations.As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments,a BWR model and simulation environment closely resembling real life conditions would be beneficial.The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer's perspective.First,the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented.This was then followed by the design of a fuzzy logic-based control built on a model-based control loop.The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories,as well as to show possible ways of further improving the controller performance.The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.展开更多
为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容...为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容量(state of charge,SOC)的状态作为模糊逻辑算法的输入,对均衡电流的约束条件进行调节;再次,基于FAMPC均衡控制方法,直接利用开关管的占空比作为系统输入;最后,在改变电池组状态并不使用额外电流控制机制的情况下进行仿真实验。结果表明,与传统的模糊控制方法相比,所提系统在正常条件下均衡速度提高了约24.51%,在电池低SOC的极端条件下均衡速度可以进一步提高至34.48%。所提系统将模糊算法提供的稳定性与模型预测控制算法的快速性相结合,保证了电池组更安全稳定的运行,可为电池组性能提升研究提供参考。展开更多
有源电力滤波器(active power filter,APF)的控制方法是决定其补偿性能的关键因素之一。该文基于单相APF的Euler-Lagrange(EL)系统状态平均模型,提出了一种无源性控制新方法。该方法首先基于替代定理建立了考虑源阻抗和非线性负荷影响...有源电力滤波器(active power filter,APF)的控制方法是决定其补偿性能的关键因素之一。该文基于单相APF的Euler-Lagrange(EL)系统状态平均模型,提出了一种无源性控制新方法。该方法首先基于替代定理建立了考虑源阻抗和非线性负荷影响的单相APFEL系统状态平均模型,在此基础上设计了无源性间接控制律,确保对单相APF控制目标的渐近跟踪。由于在线计算直流电容指令电压波动量十分困难,在控制方法的执行中忽略波动量的影响,简化了控制方法的实现;此外,该方法还研究了所注入的阻尼大小对控制效果的影响以及APF内层控制过调制产生的原因,针对无源性控制律跟踪精度的要求与内层控制过调制限幅条件间的矛盾,通过构造模糊逻辑推理环节实现阻尼系数的在线调整,在满足内层控制限幅条件下确保跟踪精度和补偿效果。仿真结果验证了所提出方法的正确性和有效性。展开更多
基金support through the ARC Linkage LP0989780 grant titled "The study anddevelopment of a 3-D real-time stockpile management system"the support in part from Institute for Mineral and Energy Resources,University of Adelaide 2009-2010,as well as Faculty of Engineering,Computer and Mathematical Sciences strategic research funding,2010
文摘The bucket wheel reclaimer(BWR) is a key piece of equipment which has been widely used for stacking and reclaiming bulk materials(i.e.iron ore and coal) in places such as ports,iron-steel plants,coal storage areas,and power stations from stockpiles.BWRs are very large in size,heavy in weight,expensive in price,and slow in motion.There are many challenges in attempting to automatically control their motion to accurately follow the required trajectories involving uncertain parameters from factors such as friction,turbulent wind,its own dynamics,and encoder limitations.As BWRs are always heavily engaged in production and cannot be spared very long for motion control studies and associated developments,a BWR model and simulation environment closely resembling real life conditions would be beneficial.The following research focused mainly on the implementation of fuzzy logic to a BWR motion control from an engineer's perspective.First,the modeling of a BWR including partially known parameters such as friction force and turbulence to the system was presented.This was then followed by the design of a fuzzy logic-based control built on a model-based control loop.The investigation provides engineers with an example of applying fuzzy logic in a model based approach to properly control the motion of a large BWR following defined trajectories,as well as to show possible ways of further improving the controller performance.The result indicates that fuzzy logic can be applied easily by engineers to overcome most motion control issues involving a large BWR.
文摘为了提升锂离子电池组均衡系统的性能,提出了一种基于模糊自适应模型预测控制(fuzzy adaptive model predictive control,FAMPC)的模块化均衡系统。首先,由改进的buck-boost电路和反激变压器组成双层均衡拓扑结构;其次,以不同电池剩余容量(state of charge,SOC)的状态作为模糊逻辑算法的输入,对均衡电流的约束条件进行调节;再次,基于FAMPC均衡控制方法,直接利用开关管的占空比作为系统输入;最后,在改变电池组状态并不使用额外电流控制机制的情况下进行仿真实验。结果表明,与传统的模糊控制方法相比,所提系统在正常条件下均衡速度提高了约24.51%,在电池低SOC的极端条件下均衡速度可以进一步提高至34.48%。所提系统将模糊算法提供的稳定性与模型预测控制算法的快速性相结合,保证了电池组更安全稳定的运行,可为电池组性能提升研究提供参考。
文摘有源电力滤波器(active power filter,APF)的控制方法是决定其补偿性能的关键因素之一。该文基于单相APF的Euler-Lagrange(EL)系统状态平均模型,提出了一种无源性控制新方法。该方法首先基于替代定理建立了考虑源阻抗和非线性负荷影响的单相APFEL系统状态平均模型,在此基础上设计了无源性间接控制律,确保对单相APF控制目标的渐近跟踪。由于在线计算直流电容指令电压波动量十分困难,在控制方法的执行中忽略波动量的影响,简化了控制方法的实现;此外,该方法还研究了所注入的阻尼大小对控制效果的影响以及APF内层控制过调制产生的原因,针对无源性控制律跟踪精度的要求与内层控制过调制限幅条件间的矛盾,通过构造模糊逻辑推理环节实现阻尼系数的在线调整,在满足内层控制限幅条件下确保跟踪精度和补偿效果。仿真结果验证了所提出方法的正确性和有效性。
