A direct drive actuator （DDA） with direct drive valves （DDVs） as the control device is an ideal solution for a flight actuation system. This paper presents a novel triple-redundant voice coil motor （TRVCM） used ...A direct drive actuator （DDA） with direct drive valves （DDVs） as the control device is an ideal solution for a flight actuation system. This paper presents a novel triple-redundant voice coil motor （TRVCM） used for redundant DDVs. The TRVCM features electrical/mechanical hybrid triple-redundancy by securing three stators along with three moving coils in the same frame. A permanent magnet （PM） Halbach array is employed in each redundant VCM to simplify the system structure. A back-to-back design between neighborly redundancies is adopted to decouple the magnetic flux linkage. The particle swarm optimization （PSO） method is implemented to optimize design parameters based on the analytical magnetic circuit model. The optimization objective function is defined as the acceleration capacity of the motor to achieve high dynamic performance. The optimal geometric parameters are verified with 3D magnetic field finite element analysis （FEA）. A research prototype has been developed for experimental purpose. The experimental results of magnetic field density and force output show that the proposed TRVCM has great potential of applications in DDA systems.展开更多
针对冗余直接驱动阀伺服系统中由于余度降级所造成的性能降低问题,提出一种神经网络自适应滑模余度控制策略.利用径向基函数神经网络RBFNN(Radial Basis Function Neural Network)的在线学习功能,对系统发生的变化进行快速自适应补偿,...针对冗余直接驱动阀伺服系统中由于余度降级所造成的性能降低问题,提出一种神经网络自适应滑模余度控制策略.利用径向基函数神经网络RBFNN(Radial Basis Function Neural Network)的在线学习功能,对系统发生的变化进行快速自适应补偿,使系统状态趋近于滑模面,提高跟踪精度和鲁棒性;并通过与比例微分PD(Proportional-Derivative)算法的并行控制,促进RBFNN的收敛,增强系统的稳定性.通过与PID(Proportional-Integral-Deriva-tive)切换控制策略的对比研究,表明RBFNN自适应滑模余度控制方法不但设计简单,而且能够有效克服余度降级带来的系统性能下降的问题,极大地改善了系统的品质.展开更多
基金supported by National Science Foundation for Distinguished Young Scholars of China(No.50825502)National Natural Science Foundation of China(No.51105016)
文摘A direct drive actuator （DDA） with direct drive valves （DDVs） as the control device is an ideal solution for a flight actuation system. This paper presents a novel triple-redundant voice coil motor （TRVCM） used for redundant DDVs. The TRVCM features electrical/mechanical hybrid triple-redundancy by securing three stators along with three moving coils in the same frame. A permanent magnet （PM） Halbach array is employed in each redundant VCM to simplify the system structure. A back-to-back design between neighborly redundancies is adopted to decouple the magnetic flux linkage. The particle swarm optimization （PSO） method is implemented to optimize design parameters based on the analytical magnetic circuit model. The optimization objective function is defined as the acceleration capacity of the motor to achieve high dynamic performance. The optimal geometric parameters are verified with 3D magnetic field finite element analysis （FEA）. A research prototype has been developed for experimental purpose. The experimental results of magnetic field density and force output show that the proposed TRVCM has great potential of applications in DDA systems.
文摘针对冗余直接驱动阀伺服系统中由于余度降级所造成的性能降低问题,提出一种神经网络自适应滑模余度控制策略.利用径向基函数神经网络RBFNN(Radial Basis Function Neural Network)的在线学习功能,对系统发生的变化进行快速自适应补偿,使系统状态趋近于滑模面,提高跟踪精度和鲁棒性;并通过与比例微分PD(Proportional-Derivative)算法的并行控制,促进RBFNN的收敛,增强系统的稳定性.通过与PID(Proportional-Integral-Deriva-tive)切换控制策略的对比研究,表明RBFNN自适应滑模余度控制方法不但设计简单,而且能够有效克服余度降级带来的系统性能下降的问题,极大地改善了系统的品质.
