Iterative Learning Control （ILC） captures interests of many scholars because of its capability of high precision control implement without identifying plant mathematical models, and it is widely applied in control e...Iterative Learning Control （ILC） captures interests of many scholars because of its capability of high precision control implement without identifying plant mathematical models, and it is widely applied in control engineering. Presently, most ILC algorithms still follow the original ideas of ARIMOTO, in which the iterative-learning-rate is composed by the control error with its derivative and integral values. This kind of algorithms will result in inevitable problems such as huge computation, big storage capacity for algorithm data, and also weak robust. In order to resolve these problems, an improved iterative learning control algorithm with fixed step is proposed here which breaks the primary thought of ARIMOTO. In this algorithm, the control step is set only according to the value of the control error, which could enormously reduce the computation and storage size demanded, also improve the robust of the algorithm by not using the differential coefficient of the iterative learning error. In this paper, the convergence conditions of this proposed fixed step iterative learning algorithm is theoretically analyzed and testified. Then the algorithm is tested through simulation researches on a time-variant object with randomly set disturbance through calculation of step threshold value, algorithm robustness testing,and evaluation of the relation between convergence speed and step size. Finally the algorithm is validated on a valve-serving-cylinder system of a joint robot with time-variant parameters. Experiment results demonstrate the stability of the algorithm and also the relationship between step value and convergence rate. Both simulation and experiment testify the feasibility and validity of the new algorithm proposed here. And it is worth to noticing that this algorithm is simple but with strong robust after improvements, which provides new ideas to the research of iterative learning control algorithms.展开更多
A new SOI （Silicon On Insulator） high voltage device with Step Unmovable Surface Charges （SUSC） of buried oxide layer and its analytical breakdown model are proposed in the paper. The unmovable charges are impleme...A new SOI （Silicon On Insulator） high voltage device with Step Unmovable Surface Charges （SUSC） of buried oxide layer and its analytical breakdown model are proposed in the paper. The unmovable charges are implemented into the upper surface of buried oxide layer to increase the vertical electric field and uniform the lateral one. The 2-D Poisson＇s equation is solved to demonstrate the modulation effect of the immobile interface charges and analyze the electric field and breakdown voltage with the various geometric parameters and step numbers. A new RESURF （REduce SURface Field） condition of the SOl device considering the interface charges and buried oxide is derived to maximize breakdown voltage. The analytical results are in good agreement with the numerical analysis obtained by the 2-D semiconductor devices simulator MEDICI. As a result, an 1200V breakdown voltage is firstly obtained in 3pro-thick top Si layer, 2pro-thick buried oxide layer and 70pro-length drift region using a linear doping profile of unmovable buried oxide charges.展开更多
基金supported by Specialized Research Fund for Doctoral Program of Higher Education of China (Grant No. 20091102120038)
文摘Iterative Learning Control （ILC） captures interests of many scholars because of its capability of high precision control implement without identifying plant mathematical models, and it is widely applied in control engineering. Presently, most ILC algorithms still follow the original ideas of ARIMOTO, in which the iterative-learning-rate is composed by the control error with its derivative and integral values. This kind of algorithms will result in inevitable problems such as huge computation, big storage capacity for algorithm data, and also weak robust. In order to resolve these problems, an improved iterative learning control algorithm with fixed step is proposed here which breaks the primary thought of ARIMOTO. In this algorithm, the control step is set only according to the value of the control error, which could enormously reduce the computation and storage size demanded, also improve the robust of the algorithm by not using the differential coefficient of the iterative learning error. In this paper, the convergence conditions of this proposed fixed step iterative learning algorithm is theoretically analyzed and testified. Then the algorithm is tested through simulation researches on a time-variant object with randomly set disturbance through calculation of step threshold value, algorithm robustness testing,and evaluation of the relation between convergence speed and step size. Finally the algorithm is validated on a valve-serving-cylinder system of a joint robot with time-variant parameters. Experiment results demonstrate the stability of the algorithm and also the relationship between step value and convergence rate. Both simulation and experiment testify the feasibility and validity of the new algorithm proposed here. And it is worth to noticing that this algorithm is simple but with strong robust after improvements, which provides new ideas to the research of iterative learning control algorithms.
基金Supported by the National Natural Science Foundation of China (No.60276040).
文摘A new SOI （Silicon On Insulator） high voltage device with Step Unmovable Surface Charges （SUSC） of buried oxide layer and its analytical breakdown model are proposed in the paper. The unmovable charges are implemented into the upper surface of buried oxide layer to increase the vertical electric field and uniform the lateral one. The 2-D Poisson＇s equation is solved to demonstrate the modulation effect of the immobile interface charges and analyze the electric field and breakdown voltage with the various geometric parameters and step numbers. A new RESURF （REduce SURface Field） condition of the SOl device considering the interface charges and buried oxide is derived to maximize breakdown voltage. The analytical results are in good agreement with the numerical analysis obtained by the 2-D semiconductor devices simulator MEDICI. As a result, an 1200V breakdown voltage is firstly obtained in 3pro-thick top Si layer, 2pro-thick buried oxide layer and 70pro-length drift region using a linear doping profile of unmovable buried oxide charges.
