伴随着光纤技术的快速发展,光纤网络已部署于航空航天、舰船、数据中心和工业物联网中。传统的光时域反射仪(optical time domain reflectometer,OTDR)因原理限制,难以实现高分辨率测试,在上述复杂场景中应用受限。基于瑞利散射的光频...伴随着光纤技术的快速发展,光纤网络已部署于航空航天、舰船、数据中心和工业物联网中。传统的光时域反射仪(optical time domain reflectometer,OTDR)因原理限制,难以实现高分辨率测试,在上述复杂场景中应用受限。基于瑞利散射的光频域反射(optical frequency domain reflection,OFDR)技术可实现极高的空间分辨率、高传感灵敏度和快速的测试速率,该系列产品适用于光器件、光模块、短距离光网络的测试和故障排除,可实现从器件到光学链路全范围的插损、回损和长度测量。文中基于光频域反射法原理设计实现了一套光纤链路检测系统,针对偏振衰落效应和激光器非线性扫频等难题进行了研究,在112 m的测试链路上实现了20μm空间分辨率。展开更多
This paper focuses on designing an adaptive radial basis function neural network(RBFNN) control method for a class of nonlinear systems with unknown parameters and bounded disturbances. The problems raised by the unkn...This paper focuses on designing an adaptive radial basis function neural network(RBFNN) control method for a class of nonlinear systems with unknown parameters and bounded disturbances. The problems raised by the unknown functions and external disturbances in the nonlinear system are overcome by RBFNN, combined with the single parameter direct adaptive control method. The novel adaptive control method is designed to reduce the amount of computations effectively.The uniform ultimate boundedness of the closed-loop system is guaranteed by the proposed controller. A coupled motor drives(CMD) system, which satisfies the structure of nonlinear system,is taken for simulation to confirm the effectiveness of the method.Simulations show that the developed adaptive controller has favorable performance on tracking desired signal and verify the stability of the closed-loop system.展开更多
文摘伴随着光纤技术的快速发展,光纤网络已部署于航空航天、舰船、数据中心和工业物联网中。传统的光时域反射仪(optical time domain reflectometer,OTDR)因原理限制,难以实现高分辨率测试,在上述复杂场景中应用受限。基于瑞利散射的光频域反射(optical frequency domain reflection,OFDR)技术可实现极高的空间分辨率、高传感灵敏度和快速的测试速率,该系列产品适用于光器件、光模块、短距离光网络的测试和故障排除,可实现从器件到光学链路全范围的插损、回损和长度测量。文中基于光频域反射法原理设计实现了一套光纤链路检测系统,针对偏振衰落效应和激光器非线性扫频等难题进行了研究,在112 m的测试链路上实现了20μm空间分辨率。
基金partially supported by the National Natural Science Foundation of China(61703402,61374048)
文摘This paper focuses on designing an adaptive radial basis function neural network(RBFNN) control method for a class of nonlinear systems with unknown parameters and bounded disturbances. The problems raised by the unknown functions and external disturbances in the nonlinear system are overcome by RBFNN, combined with the single parameter direct adaptive control method. The novel adaptive control method is designed to reduce the amount of computations effectively.The uniform ultimate boundedness of the closed-loop system is guaranteed by the proposed controller. A coupled motor drives(CMD) system, which satisfies the structure of nonlinear system,is taken for simulation to confirm the effectiveness of the method.Simulations show that the developed adaptive controller has favorable performance on tracking desired signal and verify the stability of the closed-loop system.
