Hierarchical modeling and speed control of networked induction motor systems

This paper proposes a hierarchical modeling method and a fuzzy speed control strategy for nonlinear networked induction motor systems subject to network induced time delay and packets dropout. The networked induction motor control system consists of a networked speed controller and a local controller. Fuzzy gain scheduling is applied on the networked speed controller to guarantee the robustness against complicated variations on the communication network. The state predictor is to compensate the time delay occurred in data transmission in the feedback channel. In stability analysis, the upper allowed limits of the time delay and packets dropout are calculated using the Lyapunov-Krasovskii theorem, respectively. Simulation and experimental results are given to illustrate the effectiveness of the proposed approach

Scheduling and control co-design of networked induction motor control systems

This paper investigates the co-design of remote speed control and network scheduling for motion coordination of multiple induction motors through a shared communication network. An integrated feedback scheduling algorithm is designed to allocate the optimal sampling period and priority to each control loop to optimize the global performance of a networked control system (NCS), while satisfying the constraints of stability and schedulability. The rational gain of the network speed controllers is calculated using the Lyapunov theorem and online tuned by fuzzy logic to guarantee the robustness against complicated variations on the communication network. Furthermore, a state predictor is designed to compensate the time delay occurred in data transmission from the sensor to the controller, as a part of the networked controller. Simulation results are given to illustrate the effectiveness of the proposed control-and-scheduling co-design approach

Hierarchical modeling and speed control of networked induction motor systems

This paper proposes a hierarchical modeling method and a fuzzy speed control strategy for nonlinear networked induction motor systems subject to network induced time delay and packets dropout. The networked induction motor control system consists of a networked speed controller and a local controller. Fuzzy gain scheduling is applied on the networked speed controller to guarantee the robustness against complicated variations on the communication network. The state predictor is to compensate the time delay occurred in data transmission in the feedback channel. In stability analysis, the upper allowed limits of the time delay and packets dropout are calculated using the Lyapunov-Krasovskii theorem, respectively. Simulation and experimental results are given to illustrate the effectiveness of the proposed approach

Integrated feedback scheduling and control co-design for motion coordination of networked induction motor systems

This paper investigates the codesign of remote speed control and network scheduling for motion coordination of multiple induction motors through a shared communication network. An integrated feedback scheduling algorithm is designed to allocate the optimal sampling period and priority to each control loop to optimize the global performance of a networked control system (NCS), while satisfying the constraints of stability and schedulability. A speed synchronization method is incorporated into the scheduling algorithm to improve the speed synchronization performance of multiple induction motors. The rational gain of the network speed controllers is calculated using the Lyapunov theorem and tuned online by fuzzy logic to guarantee the robustness against complicated variations on the communication network. Furthermore, a state predictor is designed to compensate the time delay which occurred in data transmission from the sensor to the controller, as a part of the networked controller. Simulation results support the effectiveness of the proposed control-and-scheduling codesign approach

Fuzzy speed control of networked motion control systems

This paper proposed an integrated scheme for the modeling and control of induction motors in the networked environment. The networked control system (NCS) is built in hierarchical structure, which consists ofa networked speed controller and a local controller. In the networked speed controller, fuzzy gain scheduling is applied to guarantee the robustness against communication constraints. Furthermore, a state predictor is designed to compensate the time delay occurred in data transmission from the sensor to the controller, as a component ofthe networked speed controller. Simulation and experimental results are given to illustrate the effectiveness ofthe proposed approach