A robust control strategy using the second-order integral sliding mode control(SOISMC)based on the variable speed grey wolf optimization(VGWO)is proposed.The aim is to maximize the wind power extraction of wind turbin...A robust control strategy using the second-order integral sliding mode control(SOISMC)based on the variable speed grey wolf optimization(VGWO)is proposed.The aim is to maximize the wind power extraction of wind turbine.Firstly,according to the uncertainty model of wind turbine,a SOISMC torque controller with fast convergence speed,strong robustness and effective chattering reduction is designed,which ensures that the torque controller can effectively track the reference speed.Secondly,given the strong local search ability of the grey wolf optimization(GWO)and the fast convergence speed and strong global search ability of the particle swarm optimization(PSO),the speed component of PSO is introduced into GWO,and VGWO with fast convergence speed,high solution accuracy and strong global search ability is used to optimize the parameters of wind turbine torque controller.Finally,the simulation is implemented based on Simulink/SimPowerSystem.The results demonstrate the effectiveness of the proposed strategy under both external disturbance and model uncertainty.展开更多
We investigate the optimal joint power allocation in Heterogeneous Networks （HetNets） to maximise its capacity. Consider- ing frequency reuse in the network, we study two power-constraint cases, i.e., per-cell po- w...We investigate the optimal joint power allocation in Heterogeneous Networks （HetNets） to maximise its capacity. Consider- ing frequency reuse in the network, we study two power-constraint cases, i.e., per-cell po- wer constraint case and per-tier power con- straint case. We formulate the capacity maxi- mization problem by allowing each subcarrier of Marco eNodeB （MeNB） to be shared by users from multiple Picos. We mathematically demonstrate that the optimal power allocation in the per-cell power constraint case has a re- markably simple nature： each Pico transmits to its user with maximum power, while MeNB either selects only one user to jointly transmit with maximum power or does not transmit to any user. In the per-tier power constraint case, the difference is that the power allocation be- tween two Picos takes the form of water-fill- ing. Numerical results verify that our proposed schemes outperform the conventional interfe- rence coordination schemes.展开更多
基金This work was supported by the National Natural Science Foundation of China(No.51876089)the Fundamental Research Funds for the Central Universities(No.kfjj20190205).
文摘A robust control strategy using the second-order integral sliding mode control(SOISMC)based on the variable speed grey wolf optimization(VGWO)is proposed.The aim is to maximize the wind power extraction of wind turbine.Firstly,according to the uncertainty model of wind turbine,a SOISMC torque controller with fast convergence speed,strong robustness and effective chattering reduction is designed,which ensures that the torque controller can effectively track the reference speed.Secondly,given the strong local search ability of the grey wolf optimization(GWO)and the fast convergence speed and strong global search ability of the particle swarm optimization(PSO),the speed component of PSO is introduced into GWO,and VGWO with fast convergence speed,high solution accuracy and strong global search ability is used to optimize the parameters of wind turbine torque controller.Finally,the simulation is implemented based on Simulink/SimPowerSystem.The results demonstrate the effectiveness of the proposed strategy under both external disturbance and model uncertainty.
基金supported by the National Major Science and Technology Project under Grant No.2009ZX03003-003-01Huawei Innovation Project under Grant No.YJCB2011060WL
文摘We investigate the optimal joint power allocation in Heterogeneous Networks （HetNets） to maximise its capacity. Consider- ing frequency reuse in the network, we study two power-constraint cases, i.e., per-cell po- wer constraint case and per-tier power con- straint case. We formulate the capacity maxi- mization problem by allowing each subcarrier of Marco eNodeB （MeNB） to be shared by users from multiple Picos. We mathematically demonstrate that the optimal power allocation in the per-cell power constraint case has a re- markably simple nature： each Pico transmits to its user with maximum power, while MeNB either selects only one user to jointly transmit with maximum power or does not transmit to any user. In the per-tier power constraint case, the difference is that the power allocation be- tween two Picos takes the form of water-fill- ing. Numerical results verify that our proposed schemes outperform the conventional interfe- rence coordination schemes.
