自适应模糊PID控制在AUV控制中的应用

自治潜水器(AUV,Autonomous Underwater Vehicle)是非线性、强耦合、大惯性的多输入多输出系统,又由于受到海流、传感器、执行机构等不确定性的影响,对AUV控制器的鲁棒性能提出了更高的要求。本文针对我国正在研制开发的长航程自治潜水器的特性及其对航行控制的要求,将PID控制与模糊控制的简便性、灵活性以及鲁棒性结合起来,为AUV设计了可在线修改PID参数的自适应模糊PID控制器,仿真结果证明了该种控制方法不但提高了AUV系统的动态特性,而且可在参数摄动和外界扰动时获得较好的控制性能。

Central-Tapped Node Linked Modular Fault-Tolerance Topology for SRM Applications

Electric vehicles (EVs) and hybrid electric vehicles (HEVs) can reduce greenhouse gas emissions while switched reluctance motor (SRM) is one of the promising motor for such applications. This paper presents a novel SRM fault-diagnosis and fault-tolerance operation solution. Based on the traditional asymmetric half-bridge topology for the SRM driving, the central tapped winding of the SRM in modular half-bridge configuration are introduced to provide fault-diagnosis and fault-tolerance functions, which are set idle in normal conditions. The fault diagnosis can be achieved by detecting the characteristic of the excitation and demagnetization currents. An SRM fault-tolerance operation strategy is also realized by the proposed topology, which compensates for the missing phase torque under the open-circuit fault, and reduces the unbalanced phase current under the short-circuit fault due to the uncontrolled faulty phase. Furthermore, the current sensor placement strategy is also discussed to give two placement methods for low cost or modular structure. Simulation results in MATLAB/Simulink and experiments on a 750-W SRM validate the effectiveness of the proposed strategy, which may have significant implications and improve the reliability of EVs/HEVs.

Estimation of electrical machine speed using sensorless technology and neural networks

The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.

Estudo comparativo de medição de força de corte no processo de retificação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)