Based on nominal model, a novel global sliding mode controller （GSMC） with a new control scheme is proposed for a practical uncertain servo system. This control scheme consists of two combined controllers, One is th...Based on nominal model, a novel global sliding mode controller （GSMC） with a new control scheme is proposed for a practical uncertain servo system. This control scheme consists of two combined controllers, One is the global sliding mode controller for practical plant, the other is the integral backstepping controller for nominal model. Modeling error between practical plant and nominal model is used to design GSMC. The steady-state control accuracy can be guaranteed by the integral backstepping control law, and the global robustness can be obtained by GSMC. The stability of the proposed controller is proved according to the Lyapunov approach. The simulation results both of sine signal and step signal tracking for 3-axis flight table are investigated to show good position tracking performance and high robustness with respect to large and parameter changes over all the response time.展开更多
The Monte Carlo study evaluates the relative accuracy of Warm＇s （1989） weighted likelihood estimate （WLE） compared to the maximum likelihood estimate （MLE） using the nominal response model. And the results indi...The Monte Carlo study evaluates the relative accuracy of Warm＇s （1989） weighted likelihood estimate （WLE） compared to the maximum likelihood estimate （MLE） using the nominal response model. And the results indicate that WLE was more accurate than MLE.展开更多
Dear Editor,H_(∞)This letter develops a new framework for the robust stability and performance conditions as well as the relevant controller synthesis with respect to uncertain robot manipulators.There often exist mo...Dear Editor,H_(∞)This letter develops a new framework for the robust stability and performance conditions as well as the relevant controller synthesis with respect to uncertain robot manipulators.There often exist model uncertainties between the nominal model and the real robot manipulator and disturbances. Hence, dealing with their effects plays a crucial role in leading to high tracking performances, as discussed in [1]–[5].展开更多
Treating plant dynamics as an ideal integrator chain disturbed by the total disturbance is the hallmark of active disturbance rejection control(ADRC).To interpret its effectiveness and success,to explain why so many v...Treating plant dynamics as an ideal integrator chain disturbed by the total disturbance is the hallmark of active disturbance rejection control(ADRC).To interpret its effectiveness and success,to explain why so many vastly different dynamic systems can be treated in this manner,and to answer why a detailed,accurate,and global mathematical model is unnecessary,is the target of this paper.Driven by a motivating example,the notions of normality and locality are introduced.Normality shows that,in ADRC,the plant is normalized to an integrator chain,which is called local nominal model and locally describes the plant’s frequency response in the neighborhood of the expected gain crossover frequency.Locality interprets why ADRC can design the controller only with the local information of the plant.With normality and locality,ADRC can be effective and robust,and obtain operational stability discussed by T.S.Tsien.Then viewing proportional-integral-derivative(PID)control as a low-frequency approximation of second-order linear ADRC,the above results are extended to PID control.A controller design framework is proposed to obtain the controller in three steps:(1)choose an integrator chain as the local nominal model of the plant;(2)select a controller family corresponding to the local nominal model;and(3)tune the controller to guarantee the gain crossover frequency specification.The second-order linear ADRC and the PID control are two special cases of the framework.展开更多
文摘Based on nominal model, a novel global sliding mode controller （GSMC） with a new control scheme is proposed for a practical uncertain servo system. This control scheme consists of two combined controllers, One is the global sliding mode controller for practical plant, the other is the integral backstepping controller for nominal model. Modeling error between practical plant and nominal model is used to design GSMC. The steady-state control accuracy can be guaranteed by the integral backstepping control law, and the global robustness can be obtained by GSMC. The stability of the proposed controller is proved according to the Lyapunov approach. The simulation results both of sine signal and step signal tracking for 3-axis flight table are investigated to show good position tracking performance and high robustness with respect to large and parameter changes over all the response time.
文摘The Monte Carlo study evaluates the relative accuracy of Warm＇s （1989） weighted likelihood estimate （WLE） compared to the maximum likelihood estimate （MLE） using the nominal response model. And the results indicate that WLE was more accurate than MLE.
基金support by “R&D Program for Forest Science Technology(RS-2024-0040 3460)” provided by Korea Forest Service(Korea Forestry Promotion Institute)
文摘Dear Editor,H_(∞)This letter develops a new framework for the robust stability and performance conditions as well as the relevant controller synthesis with respect to uncertain robot manipulators.There often exist model uncertainties between the nominal model and the real robot manipulator and disturbances. Hence, dealing with their effects plays a crucial role in leading to high tracking performances, as discussed in [1]–[5].
基金This work was supported by the National Nature Science Foundation of China(Grant No.61733017).
文摘Treating plant dynamics as an ideal integrator chain disturbed by the total disturbance is the hallmark of active disturbance rejection control(ADRC).To interpret its effectiveness and success,to explain why so many vastly different dynamic systems can be treated in this manner,and to answer why a detailed,accurate,and global mathematical model is unnecessary,is the target of this paper.Driven by a motivating example,the notions of normality and locality are introduced.Normality shows that,in ADRC,the plant is normalized to an integrator chain,which is called local nominal model and locally describes the plant’s frequency response in the neighborhood of the expected gain crossover frequency.Locality interprets why ADRC can design the controller only with the local information of the plant.With normality and locality,ADRC can be effective and robust,and obtain operational stability discussed by T.S.Tsien.Then viewing proportional-integral-derivative(PID)control as a low-frequency approximation of second-order linear ADRC,the above results are extended to PID control.A controller design framework is proposed to obtain the controller in three steps:(1)choose an integrator chain as the local nominal model of the plant;(2)select a controller family corresponding to the local nominal model;and(3)tune the controller to guarantee the gain crossover frequency specification.The second-order linear ADRC and the PID control are two special cases of the framework.
