Free-field soil response to bidirectional horizontal non-uniform ground motion from multi-point shaking table tests

Han, Junyan; Guo, Zhike; Zhong, Zilan; Naggar, M. Hesham El; Miao, Huiquan; Du, Xiuli

doi:10.1016/j.soildyn.2022.107512

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…The electro-hydraulic shaking table is the most used and reliable earthquake simulation test equipment in the field of structure anti-seismic research, especially in recent decades [1][2][3]. However, for earthquake experiments with structures with a large span such as trains, bridges and pipelines, etc., a single shaking table is not at all sufficient; thus, a shaking table array system composed of multiple identical or different shaking tables is proposed to solve this problem [4][5][6][7]. The shaking table array is more complex compared with the single shaking table system due to the tracking precision needed and also the synchronization precision needed to protect the test specimen [8].…”

Section: Introductionmentioning

confidence: 99%

Experiment Research on Complex Optimization Algorithm-Based Adaptive Iterative Learning Control for Electro-Hydraulic Shaking Tables

et al. 2023

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The adaptive iterative learning control method for electro-hydraulic shaking tables based on the complex optimization algorithm was proposed to overcome the potential stability problem of the traditional iteration control method. The system identification precision’s influence on convergence was analyzed. Based on the real optimization theory and the mapping relationship between real vector space and complex vector space, the complex Broyden optimization iterative algorithm was proposed, and its stability and convergence was analyzed. To improve the stability and accelerate the convergence of the proposed algorithm, the complex steepest descent algorithm was proposed to cooperate with the complex Broyden optimization algorithm, which can adaptively optimize the complex steepest gradient iterative gain and update the system impedance in real time during the control process. The shaking tables experiment system was designed, applying xPC target rapid prototype control technology, and a series of experimental tests were performed. The results indicated that the proposed control method can quickly and stably converge to the optimal solution no matter whether the system identification error is small or large, and, thus, verified that validity and feasibility of the proposed adaptive iterative learning method.

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