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Zhiqiang Wan,Jian Xiong,Ji Lei,Chen Chen,Kai Zhang 전력전자학회 2015 JOURNAL OF POWER ELECTRONICS Vol.15 No.5
Capacitor current feedback active damping is extensively used in grid-connected converters with an LCL filter. However, systems tends to become unstable when the digital control delay is taken into account, especially in low switching frequencies. This paper discusses this issue by deriving a discrete model with a digital control delay and by presenting the stable region of an active damping loop from high to low switching frequencies. In order to overcome the disadvantage of capacitor current feedback active damping, this paper proposes a modified approach using grid current and converter current for feedback. This can expand the stable region and provide sufficient active damping whether in high or low switching frequencies. By applying the modified approach, the active damping loop can be simplified from fourth-order into second-order, and the design of the grid current loop can be simplified. The modified approach can work well when the grid impedance varies. Both the active damping performance and the dynamic performance of the current loop are verified by simulations and experimental results.
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A Highly Efficient Aeroelastic Optimization Method Based on a Surrogate Model
Zhiqiang, Wan,Xiaozhe, Wang,Chao, Yang The Korean Society for Aeronautical and Space Scie 2016 International Journal of Aeronautical and Space Sc Vol.17 No.4
This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.
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A Highly Efficient Aeroelastic Optimization Method Based on a Surrogate Model
Wan Zhiqiang,Wang Xiaozhe,Yang Chao 한국항공우주학회 2016 International Journal of Aeronautical and Space Sc Vol.17 No.4
This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.
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