Through the in-depth study of working principle and application of pfc algorithm, the paper introduces pfc algorithm to the constant tension control of the system of shaftless driven in printer. In order to better imp...
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ISBN:
(纸本)9783037858813
Through the in-depth study of working principle and application of pfc algorithm, the paper introduces pfc algorithm to the constant tension control of the system of shaftless driven in printer. In order to better implement constant tension control of shaftless driven control system, the paper choose a first order system as the transfer function of the system of tension model. The paper carries on the silulation of the system's output of constant tension,aiming at the situation of the changing of the internal parameters of prediction model for pfc algorithm, such as the attenuation coefficient of reference trajectory, the change of fitting points, prediction horizon and so on, matching of prediction model and tension model of pfc algorithm. The simulation system provides a theoretical basis to build the actual tension control system.
The authors propose a novel multi-model direct generalised predictive control based on predictive function control (pfc) algorithm for automatic train operation system. The proposed method facilitates autonomous drivi...
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The authors propose a novel multi-model direct generalised predictive control based on predictive function control (pfc) algorithm for automatic train operation system. The proposed method facilitates autonomous driving of a train through a given guidance trajectory. Firstly, they present a multi-model architecture based on fuzzy c-means clustering algorithm. In order to obtain the optimal number of sub-linear models, they apply Xie-Beni cluster validity index. In this regards, the multi-model set is established off-line. Secondly, the proper sub-linear model is selected as the predictive model by using switching performance index at each time slot. The control variables are calculated by direct generalised predictive controller based on pfc. The control algorithm is simple, and can reduce the on-line computation time by directly identifies the unknown parameters in the controller. It can avoid recursively solving the Diophantine equations. The calculation of compensation value becomes simple by introducing pfc. Finally, simulation results are provided to show the effectiveness of the proposed scheme.
The authors propose a novel multi-model direct generalised predictive control based on predictive function control (pfc) algorithm for automatic train operation system. The proposed method facilitates autonomous drivi...
详细信息
The authors propose a novel multi-model direct generalised predictive control based on predictive function control (pfc) algorithm for automatic train operation system. The proposed method facilitates autonomous driving of a train through a given guidance trajectory. Firstly, they present a multi-model architecture based on fuzzy c-means clustering algorithm. In order to obtain the optimal number of sub-linear models, they apply Xie-Beni cluster validity index. In this regards, the multi-model set is established off-line. Secondly, the proper sub-linear model is selected as the predictive model by using switching performance index at each time slot. The control variables are calculated by direct generalised predictive controller based on pfc. The control algorithm is simple, and can reduce the on-line computation time by directly identifies the unknown parameters in the controller. It can avoid recursively solving the Diophantine equations. The calculation of compensation value becomes simple by introducing pfc. Finally, simulation results are provided to show the effectiveness of the proposed scheme.
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