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
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
The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises i...The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF （degree-of-freedom） hydraulic vibration table. The result shows that it is favorable to improve the control precision of the MIMO vibration control system.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
This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-thresho...This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.展开更多
To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to e...To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.展开更多
This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed m...This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.展开更多
This article focuses on the high accuracy quasi-synchronous control issue of multiple electrohydraulic systems(MEHS).In order to overcome the negative effects of parameter uncertainty and external load interference of...This article focuses on the high accuracy quasi-synchronous control issue of multiple electrohydraulic systems(MEHS).In order to overcome the negative effects of parameter uncertainty and external load interference of MEHS,a kind of finite-time disturbance observer(FTDO)via terminal sliding mode method is constructed based on the MEHS model to achieve fast and accuracy estimation and compensation ability.To avoid the differential explosion in backstepping iteration,the dynamic surface control is used in this paper to guarantee the follower electrohydraulic nodes synchronize to the leader motion with a better performance.Furthermore,a timevarying barrier Lyapunov function(tvBLF)is adopted during the controller design process to constraint the output tracking error of MEHS in a prescribed performance with time-varying exponential function.As the initial state condition is relax by tvBLF,the input saturation law is also adopted during the controller design process in this paper to restrain the surges of input signals,which can avoid the circuit and mechanical structure damage caused by the volatile input signal.An MEHS experimental bench is constructed to verify the effectiveness of the theoretical conclusions proposed in this paper and the advantages of the proposed conclusions in this paper are illustrated by a series of contradistinctive experimental results.展开更多
借助于偏差补偿原理和预滤波思想,推导了有色噪声干扰输出误差系统参数估计的偏差补偿递推最小二乘(Bias compensation recursive least squares,BCRLS)辨识方法.该方法降低了辨识对输入信号平稳性的要求,实现了偏差补偿方法参数估计的...借助于偏差补偿原理和预滤波思想,推导了有色噪声干扰输出误差系统参数估计的偏差补偿递推最小二乘(Bias compensation recursive least squares,BCRLS)辨识方法.该方法降低了辨识对输入信号平稳性的要求,实现了偏差补偿方法参数估计的递推计算,可以用于在线辨识.提出的递推BCRLS辨识方法优于非递推偏差补偿最小二乘算法,提高了参数估计精度.仿真试验证实了算法的有效性.展开更多
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.
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.
基金This project is supported by Program for New Century Excellent Talents in University,China(No.NCET-04-0325).
文摘The FRF estimator based on the errors-in-variables （EV） model of multi-input multi-output （MIMO） system is presented to reduce the bias error of FRF HI estimator. The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF （degree-of-freedom） hydraulic vibration table. The result shows that it is favorable to improve the control precision of the MIMO vibration control system.
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.
基金This work was supported by the National Natural Science Foundation of China(62076025).
文摘This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.
基金Supported by the National Thousand Talents Program of Chinathe National Natural Science Foundation of China(61473054)the Fundamental Research Funds for the Central Universities of China
文摘To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.
文摘This paper develops a feedforward neural network based input output model for a general unknown nonlinear dynamic system identification when only the inputs and outputs are accessible observations. In the developed model, the size of the input space is directly related to the system order. By monitoring the identification error characteristic curve, we are able to determine the system order and subsequently an appropriate network structure for systems identification. Simulation results are promising and show that generic nonlinear systems can be identified, different cases of the same system can also be discriminated by our model.
基金This study was co-supported by the National Natural Science Foundation of China(Nos.52175046,51975024,and 12072068)Sichuan Science and Technology Program(Nos.2022JDRC0018 and 2022YFG0341).
文摘This article focuses on the high accuracy quasi-synchronous control issue of multiple electrohydraulic systems(MEHS).In order to overcome the negative effects of parameter uncertainty and external load interference of MEHS,a kind of finite-time disturbance observer(FTDO)via terminal sliding mode method is constructed based on the MEHS model to achieve fast and accuracy estimation and compensation ability.To avoid the differential explosion in backstepping iteration,the dynamic surface control is used in this paper to guarantee the follower electrohydraulic nodes synchronize to the leader motion with a better performance.Furthermore,a timevarying barrier Lyapunov function(tvBLF)is adopted during the controller design process to constraint the output tracking error of MEHS in a prescribed performance with time-varying exponential function.As the initial state condition is relax by tvBLF,the input saturation law is also adopted during the controller design process in this paper to restrain the surges of input signals,which can avoid the circuit and mechanical structure damage caused by the volatile input signal.An MEHS experimental bench is constructed to verify the effectiveness of the theoretical conclusions proposed in this paper and the advantages of the proposed conclusions in this paper are illustrated by a series of contradistinctive experimental results.
文摘借助于偏差补偿原理和预滤波思想,推导了有色噪声干扰输出误差系统参数估计的偏差补偿递推最小二乘(Bias compensation recursive least squares,BCRLS)辨识方法.该方法降低了辨识对输入信号平稳性的要求,实现了偏差补偿方法参数估计的递推计算,可以用于在线辨识.提出的递推BCRLS辨识方法优于非递推偏差补偿最小二乘算法,提高了参数估计精度.仿真试验证实了算法的有效性.
