Self-sensing for electromagnetic actuators. Part I: A coupled reluctance network model approach

A self-sensing arrangement in active magnetic bearings (AMBs) comprises a single electromagnetic transducer to realize the actuation and sensing functions concurrently. Minimizing the number of sensing devices and associated interfacing directly reduces possible failure points, system costs, and system complexity. Currently, self-sensing performance is degraded due to problems such as magnetic cross-coupling, eddy currents, saturation, and high losses. This first paper in a two part series presents an integrated model for self-sensing of an 8-pole heteropolar magnetic bearing. The proposed self-sensing approach addresses mechanisms that contribute to modelling error and uncertainty by using several techniques in an integrated structure. A coupled reluctance network model (RNM) is developed which models the coil impedance at the switching frequency. The accuracy of the model is improved by incorporating terms for air gap fringing, complex permeability, and magnetic material nonlinearity. The RNM is verified and refined through a process of iteration using finite element method (FEM) results and experimental AMB measurements. The results demonstrate that a RNM with only 40 nodes can achieve high levels of accuracy when compared to an 80 000 node FEM analysis.In Part II of the series, the refined RNM is incorporated into a multiple input multiple output (MIMO) parameter estimation self-sensing scheme.     

电子政务系统中角色网络扩展模型研究*

从当前角色网络模型(RNM)所存在的问题入手,通过加入时限约束和解决角色间继承关系上的缺陷对角色网络模型进行改进,并进一步提出基于时限约束的角色网络模型(TRNM)。该模型在继承角色网络模型全部优势的同时,一方面解决了原有RNM中角色间继承关系上的缺陷,使高层角色可以部分继承底层角色的权限;另一方面则通过对时限约束特征的定义和分析,给出了在时限约束条件下TRNM的组成成员和形式化描述,最后具体给出了TRNM的开发方法流程。     

神经网络自抗扰全垫升气垫船航迹控制

针对全垫升气垫船与常规水面船相比,非线性强,可操纵性较差,设计了神经网络自抗扰航迹引导控制器及航向控制器,以提高其航迹控制效果.利用非线性跟踪微分器(TD)提取微分信号并安排过渡过程.利用扩张状态观测器(ESO)对系统内、外扰动进行观测,并进行扰动补偿.利用非线性状态误差反馈控制律(NLSEF)提供精确控制量.为了提高自抗扰控制器( ADRC)的自适应性,利用递归网模型(RNM)对系统进行辨识,根据辨识信息对ADRC控制参数进行在线整定.仿真结果表明:在强扰动作用下,所设计航迹控制系统能够使全垫升气垫船精确地保持在计划航线上,具有自适应性强、超调量小、鲁棒性强等特点.