A novel electric vehicle (EV) induction motor (IM) controller based on voltage-fed inverter is presented. It is shown that the proposed adaptive control algorithm effectively both simplifies the structure and expands ...A novel electric vehicle (EV) induction motor (IM) controller based on voltage-fed inverter is presented. It is shown that the proposed adaptive control algorithm effectively both simplifies the structure and expands the capacity of controller. The relationship between stator's voltage and that of current under rotor's flux-oriented-coordinates is first introduced, and then the structure of vector control is analyzed, in which voltage compensation is inducted as the core feedback procedure. Experiments prove that, together with a facility for realization, a smooth transition, a prompt torque response and small concussion are gained. Extensive research conducted by varying parameters that result in practical ripple is proposed in conclusion.展开更多
The focus of this paper is to build the damage identify system, which performs “system identification” to detect the positions and extens of structural damages. The identification of structural damage can be charact...The focus of this paper is to build the damage identify system, which performs “system identification” to detect the positions and extens of structural damages. The identification of structural damage can be characterized as a nonlinear process which linear prediction models such as linear regression are not suitable. However, neural network techniques may provide an effective tool for system identification. The method of damage identification using the radial basis function neural network (RBFNN) is presented in this paper. Using this method, a simple reinforced concrete structure has been tested both in the absence and presence of noise. The results show that the RBFNN identification technology can be used with related success for the solution of dynamic damage identification problems, even in the presence of a noisy identify data. Furthermore, a remote identification system based on that is set up with Java Technologies. Key words RBFNN - inteligent identification - structural damage - Brower/Server (B/S) model CLC number TP 183 Foundation item: Supported by the Natural Science Foundation of Hubei Province in China (2001ABB0778), The Science and Technology Foundation for Wuhan Young Scholar (20015005039)Biography: RAO Wen-bi (1967-), female, Ph. D, associate professor, research direction: artificial intelligence展开更多
文摘A novel electric vehicle (EV) induction motor (IM) controller based on voltage-fed inverter is presented. It is shown that the proposed adaptive control algorithm effectively both simplifies the structure and expands the capacity of controller. The relationship between stator's voltage and that of current under rotor's flux-oriented-coordinates is first introduced, and then the structure of vector control is analyzed, in which voltage compensation is inducted as the core feedback procedure. Experiments prove that, together with a facility for realization, a smooth transition, a prompt torque response and small concussion are gained. Extensive research conducted by varying parameters that result in practical ripple is proposed in conclusion.
文摘The focus of this paper is to build the damage identify system, which performs “system identification” to detect the positions and extens of structural damages. The identification of structural damage can be characterized as a nonlinear process which linear prediction models such as linear regression are not suitable. However, neural network techniques may provide an effective tool for system identification. The method of damage identification using the radial basis function neural network (RBFNN) is presented in this paper. Using this method, a simple reinforced concrete structure has been tested both in the absence and presence of noise. The results show that the RBFNN identification technology can be used with related success for the solution of dynamic damage identification problems, even in the presence of a noisy identify data. Furthermore, a remote identification system based on that is set up with Java Technologies. Key words RBFNN - inteligent identification - structural damage - Brower/Server (B/S) model CLC number TP 183 Foundation item: Supported by the Natural Science Foundation of Hubei Province in China (2001ABB0778), The Science and Technology Foundation for Wuhan Young Scholar (20015005039)Biography: RAO Wen-bi (1967-), female, Ph. D, associate professor, research direction: artificial intelligence
