Twin support vector machine(TWSVM)is a new development of support vector machine(SVM)algorithm.It has the smaller computation scale and the stronger ability to cope with unbalanced problems.In this paper,TWSVM is intr...Twin support vector machine(TWSVM)is a new development of support vector machine(SVM)algorithm.It has the smaller computation scale and the stronger ability to cope with unbalanced problems.In this paper,TWSVM is introduced into aircraft engine gas path fault diagnosis.The generalization capacity of Gauss kernel function usually used in TWSVM is relatively weak.So a mixed kernel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good learning ability.Experimental results prove that the cross validation training accuracy of TWSVM using the mixed kernel function averagely increases 2%.Grid search is usually applied in parameter optimization of TWSVM,but it heavily depends on experience.Therefore,the hybrid particle swarm algorithm is introduced.It can intelligently and rapidly find the global optimum.Experiments prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.展开更多
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
For a class of aeroengine nonlinear systems,a novel nonlinear sliding mode controller(SMC)design method based on artificial bee colony(ABC)algorithm is proposed.In view of the strong nonlinearity and uncertainty of ae...For a class of aeroengine nonlinear systems,a novel nonlinear sliding mode controller(SMC)design method based on artificial bee colony(ABC)algorithm is proposed.In view of the strong nonlinearity and uncertainty of aeroengines,sliding mode control strategy is adopted to design controller for the aeroengine.On basis of exact linearization approach,the nonlinear sliding mode controller is obtained conveniently.By using ABC algorithm,the parameters in the designed controller can be tuned to achieve optimal performance,resulting in a closedloop system with satisfactory dynamic performance and high steady accuracy.Simulation on an aeroengine verifies the effectiveness of the presented method.展开更多
基金supported by the National Natural Science Foundation of China(No.51876089)the Postgraduate Research&Practice Innovation Program of Nanjing University of Aeronautics and Astronautics(No.xcxjh20210204)the Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems(No.GZKF-202005)。
基金supported by the Fundamental Research Funds for the Central Universities(No.NS2016027)
文摘Twin support vector machine(TWSVM)is a new development of support vector machine(SVM)algorithm.It has the smaller computation scale and the stronger ability to cope with unbalanced problems.In this paper,TWSVM is introduced into aircraft engine gas path fault diagnosis.The generalization capacity of Gauss kernel function usually used in TWSVM is relatively weak.So a mixed kernel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good learning ability.Experimental results prove that the cross validation training accuracy of TWSVM using the mixed kernel function averagely increases 2%.Grid search is usually applied in parameter optimization of TWSVM,but it heavily depends on experience.Therefore,the hybrid particle swarm algorithm is introduced.It can intelligently and rapidly find the global optimum.Experiments prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.
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 Fundamental Research Funds for the Central Universities(NS2016027)
文摘For a class of aeroengine nonlinear systems,a novel nonlinear sliding mode controller(SMC)design method based on artificial bee colony(ABC)algorithm is proposed.In view of the strong nonlinearity and uncertainty of aeroengines,sliding mode control strategy is adopted to design controller for the aeroengine.On basis of exact linearization approach,the nonlinear sliding mode controller is obtained conveniently.By using ABC algorithm,the parameters in the designed controller can be tuned to achieve optimal performance,resulting in a closedloop system with satisfactory dynamic performance and high steady accuracy.Simulation on an aeroengine verifies the effectiveness of the presented method.
