The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function mod...The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function model parameters and time delay are alternately fixed to estimate each other.The instrumental variable technique is applied to guarantee consistent estimation against measurement noise.A noteworthy merit of the proposed method is that it can handle fractional time delay estimation,compared to existing methods commonly assuming that the time delay is an integer multiple of the sampling interval.The identifiability analysis for time delay is addressed and correspondingly,some guidelines are provided for practical implementation of the proposed method.Numerical and experimental examples are presented to illustrate the effectiveness of the proposed method.展开更多
Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to rea...Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.展开更多
This paper improves the iterative learning control algo-rithm for nonlinear discrete-time dynamic systemswhich proposed by D.-H.Hwang et.al.,and make itpossible to use in the system which can give output erroronly.The...This paper improves the iterative learning control algo-rithm for nonlinear discrete-time dynamic systemswhich proposed by D.-H.Hwang et.al.,and make itpossible to use in the system which can give output erroronly.Then a sufficient condition for asymptotical conve-rgence of iterative learning algorithm is proposed.Thealgotithm can be used to a class of nonlinear systems withunknown but periodic parameters.展开更多
In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law t...In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law that brings the output voltage to the desired level. Due to infinite switching occurring at the desired level, we enhanced the switching control law by allowing a sizeable output voltage ripple. We derived mathematical models that allow one to choose the desired switching frequency. In practice, the existence of the non-ideal properties of the Zeta converter results in steady-state output voltage error. By analyzing the power loss in the zeta converter, we proposed an improved switching control law that eliminates the steady-state output voltage error. The effectiveness of the proposed method is illustrated with simulation results.展开更多
文摘The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function model parameters and time delay are alternately fixed to estimate each other.The instrumental variable technique is applied to guarantee consistent estimation against measurement noise.A noteworthy merit of the proposed method is that it can handle fractional time delay estimation,compared to existing methods commonly assuming that the time delay is an integer multiple of the sampling interval.The identifiability analysis for time delay is addressed and correspondingly,some guidelines are provided for practical implementation of the proposed method.Numerical and experimental examples are presented to illustrate the effectiveness of the proposed method.
基金National Natural Science Foundation of China(No.61374044)Shanghai Science Technology Commission,China(Nos.15510722100,16111106300)
文摘Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.
文摘This paper improves the iterative learning control algo-rithm for nonlinear discrete-time dynamic systemswhich proposed by D.-H.Hwang et.al.,and make itpossible to use in the system which can give output erroronly.Then a sufficient condition for asymptotical conve-rgence of iterative learning algorithm is proposed.Thealgotithm can be used to a class of nonlinear systems withunknown but periodic parameters.
文摘In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law that brings the output voltage to the desired level. Due to infinite switching occurring at the desired level, we enhanced the switching control law by allowing a sizeable output voltage ripple. We derived mathematical models that allow one to choose the desired switching frequency. In practice, the existence of the non-ideal properties of the Zeta converter results in steady-state output voltage error. By analyzing the power loss in the zeta converter, we proposed an improved switching control law that eliminates the steady-state output voltage error. The effectiveness of the proposed method is illustrated with simulation results.
