基于T-S模糊神经网络模型的编码器故障软闭环容错控制方法

计算机应用 ›› 2014, Vol. 34 ›› Issue (12): 3646-3650.

基于T-S模糊神经网络模型的编码器故障软闭环容错控制方法

李炜¹,李青朋¹,毛海杰¹,龚建兴²

1. 兰州理工大学电气工程与信息工程学院,兰州 730050
2. 甘肃工大舞台技术工程有限公司,兰州 730050

收稿日期:2014-06-16 修回日期:2014-08-08 出版日期:2014-12-01 发布日期:2014-12-31
通讯作者: 李青朋
作者简介:李炜(1963-),女,陕西西安人,教授,博士生导师,主要研究方向:工业过程先进控制、动态系统的故障诊断与容错控制；李青朋(1987-),男,河南安阳人,硕士研究生,主要研究方向:控制系统的故障诊断与容错控制；毛海杰(1978-）,女,内蒙古赤峰人,讲师,主要研究方向:动态系统的故障诊断与容错控制；龚建兴(1968-),男,甘肃酒泉人,高级工程师,主要研究方向:舞台机械电气控制系统设计。
基金资助:
国家自然科学基金资助项目;甘肃省自然科学基金资助项目;兰州理工大学校基金资助项目

Method of soft close-loop fault-tolerant control in encoder faults based on the T-S fuzzy neural network model

LI Wei¹,LI Qingpeng¹,MAO Haijie¹,GONG Jianxing²

1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou Gansu 730050, China;
2. Gansu University of Technology Stage Technology Engineering Company Limited, Lanzhou Gansu 730050, China

Received:2014-06-16 Revised:2014-08-08 Online:2014-12-01 Published:2014-12-31
Contact: LI Qingpeng

摘要/Abstract

摘要：

针对舞台吊杆调速系统中速度反馈元件增量式编码器可能产生的丢码、断码等问题,为防止故障影响的传播,结合数据驱动技术提出了一种基于T-S模糊神经网络(T-S FNN)模型的编码器故障检测与软闭环容错控制方法。首先,利用系统正常运行时的历史数据建立系统较为精确的T-S FNN预测模型,并用实际编码器测量值与模型预测值相减获得残差信息；其次,将其残差实时数据通过改进的序贯概率比检验(SPRT)算法进行故障检测,以克服检测延迟确保故障检测的可靠性,当检测出故障时,再用T-S FNN模型的预测输出替代故障编码器的输出,实现软闭环方式下的容错运行；最后,针对编码器丢码、断码等故障,采用上述方法进行了软闭环容错控制的有效性仿真验证。仿真结果表明,该方法能够快速可靠地检测到编码器故障,并用预测的重构信息通过容错切换机制,及时、安全地以软闭环方式实现了对故障编码器的容错控制,提高了舞台吊杆调速系统运行的安全可靠性。

Abstract:

In order to solve the problem of losing codes and pausing codes in the incremental encoder which conventionally used in the stage speed boom system as speed feedback component and prevent the propagation of fault effect, a fault detection and soft close-loop fault-tolerant control method for encoder faults based on the Takagi-Sugeno Fuzzy Neural Network (T-S FNN) model combined with the data-driven technique was proposed. First, the system of T-S FNN prediction model was established by substracting the system normal operation of historical data, and achieved the residual error information by using measured values of actual encoder and predicted values. Next, encoder fault was detected by using improved Sequential Probability Ratio Test (SPRT) algorithm though the residual error real-time data information, in order to overcome the detection delay and ensure the reliability of fault detection. Then, according to the prediction model output which was used as the output of the encoder failure to accommodate the failure when fault was detected, in order to realize the soft fault-tolerant operation by using close-loop mode. At last, the encoder fault tolerant process for the losing codes and pausing codes was proved by simulation experiment effectively. The simulation results show that the method of this article can detect the encoder fault information rapidly and reliability, and switch from the fault-tolerant mechanism timely and safely by using the reconstruction of the prediction information, in order to realize the soft closed-loop fault-tolerant control of encoder failure and improve the safety and reliability of stage speed boom system operation process.

中图分类号:

TP212.1

李炜李青朋毛海杰龚建兴. 基于T-S模糊神经网络模型的编码器故障软闭环容错控制方法[J]. 计算机应用, 2014, 34(12): 3646-3650.

LI Wei LI Qingpeng MAO Haijie GONG Jianxing. Method of soft close-loop fault-tolerant control in encoder faults based on the T-S fuzzy neural network model[J]. Journal of Computer Applications, 2014, 34(12): 3646-3650.

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