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
The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parame...The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.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Project supported by the LEB Research LaboratoryDepartment of Electrical Engineering,University of Batna 2, Algeria。
文摘The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.
