Controller Link 是 OMRON 推出的一种 FA 网络,能在 PLC、计算机等节点间方便、灵活地发送和接收大容量数据包,且实时性、可靠性较高。本文对 Controller Link 的组网技术进行深入研究,详细介绍了该网络的性能、硬件配置、网络组态、...Controller Link 是 OMRON 推出的一种 FA 网络,能在 PLC、计算机等节点间方便、灵活地发送和接收大容量数据包,且实时性、可靠性较高。本文对 Controller Link 的组网技术进行深入研究,详细介绍了该网络的性能、硬件配置、网络组态、通讯链接和网络监控设计技术。展开更多
This paper presents a control method for the Doubly-fed Induction Generator connected to a dc link through a diode bridge on the stator. In this system, the rotor is fed, at the slip frequency, by a PWM electronic con...This paper presents a control method for the Doubly-fed Induction Generator connected to a dc link through a diode bridge on the stator. In this system, the rotor is fed, at the slip frequency, by a PWM electronic converter and the stator is directly connected to the dc link using a simple diode bridge. The cost of power electronics is reduced in this system when compared with the classic DFIG machine because the system uses less one PWM inverter and additionally it uses a diode bridge. The application in mind is for microgrids. Microgrids need several elements that should work together. The usual way to connect these elements is to use power electronic devices in a common dc link. This paper presents a new form for the DFIG for this application and presents a control system for the inner control loop. Simulation and experimental results show that the system can work acceptably using a stator frequency near the rated frequency of the machine.展开更多
The control law design for a near-space hypersonic vehicle（NHV） is highly challenging due to its inherent nonlinearity,plant uncertainties and sensitivity to disturbances.This paper presents a novel functional link ...The control law design for a near-space hypersonic vehicle（NHV） is highly challenging due to its inherent nonlinearity,plant uncertainties and sensitivity to disturbances.This paper presents a novel functional link network（FLN） control method for an NHV with dynamical thrust and parameter uncertainties.The approach devises a new partially-feedback-functional-link-network（PFFLN） adaptive law and combines it with the nonlinear generalized predictive control（NGPC） algorithm.The PFFLN is employed for approximating uncertainties in flight.Its weights are online tuned based on Lyapunov stability theorem for the first time.The learning process does not need any offline training phase.Additionally,a robust controller with an adaptive gain is designed to offset the approximation error.Finally,simulation results show a satisfactory performance for the NHV attitude tracking,and also illustrate the controller＇s robustness.展开更多
This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented...This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented Kalman filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which, however, is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An unscented Kalman filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetic analysis is performed in order to quantify the effect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in three-dimensional space.展开更多
文摘This paper presents a control method for the Doubly-fed Induction Generator connected to a dc link through a diode bridge on the stator. In this system, the rotor is fed, at the slip frequency, by a PWM electronic converter and the stator is directly connected to the dc link using a simple diode bridge. The cost of power electronics is reduced in this system when compared with the classic DFIG machine because the system uses less one PWM inverter and additionally it uses a diode bridge. The application in mind is for microgrids. Microgrids need several elements that should work together. The usual way to connect these elements is to use power electronic devices in a common dc link. This paper presents a new form for the DFIG for this application and presents a control system for the inner control loop. Simulation and experimental results show that the system can work acceptably using a stator frequency near the rated frequency of the machine.
基金supported by the National Natural Science Foundation of China (9071602860974106)
文摘The control law design for a near-space hypersonic vehicle（NHV） is highly challenging due to its inherent nonlinearity,plant uncertainties and sensitivity to disturbances.This paper presents a novel functional link network（FLN） control method for an NHV with dynamical thrust and parameter uncertainties.The approach devises a new partially-feedback-functional-link-network（PFFLN） adaptive law and combines it with the nonlinear generalized predictive control（NGPC） algorithm.The PFFLN is employed for approximating uncertainties in flight.Its weights are online tuned based on Lyapunov stability theorem for the first time.The learning process does not need any offline training phase.Additionally,a robust controller with an adaptive gain is designed to offset the approximation error.Finally,simulation results show a satisfactory performance for the NHV attitude tracking,and also illustrate the controller＇s robustness.
文摘This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented Kalman filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which, however, is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An unscented Kalman filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetic analysis is performed in order to quantify the effect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in three-dimensional space.
