Active control techniques are designed to calculate the controlling force by minimizing the evaluation function, which is comprised of the quadratic form of the quantity of states and the controlling forces (Kobori 1993; Yoshikawa and Imura 1994; Ikeda 2004; Seto 1998; Phillips et al. 2012). While passive controls for absorbing vibration energy provide stable performance and costs relatively less, active control has a large effect using external energy but it is needed to take care of malfunctions that cause vibration. Though active control techniques are in practical use as described in Spencer Jr. and Nagarajaiah (2003) and Thenozhi and Yu (2013), future advancements in sensors, computers, and actuators will likely lead to new control techniques for nonlinear models including bridges and building structures.
The authors proposed an active control method (Nakamura et al. 2010) using hyper vision technology (Ishii et al. 2004), which can measure displacements of structures at intervals of f 1/100–1/1,000s
The effectiveness of the method was confirmed by conducting a series of shaking table tests (Nakamura et al. 2010). This paper examines the adoption of a preview control method (Sheridan 1966; Hayase and Ichikawa 1969; Tomizuka and Rosenthal 1979; Katayama et al. 1985) that uses projected data on future external forces in an effort to improve active control performance. The improvement of vibration control performance in a multi-degree-of-freedom system is quantitatively clarified by numerical analyses, and it is confirmed that the surface seismic wave can be predicted by using ground and underground recordings of seismic waves. Similar studies (Tateishi and Nishioka 2001; Marzbanrad et al. 2004) for civil engineering structures do not address the practical application of predicting seismic waves. This study is an extension of a previous paper (Nakamura et al. 2010), and is intended to add the preview control function to the previously proposed active control system.
This study is intended to clarify the following:
1. The equations are determined to derive the preview controlling force and clarify the relation between the number of preview steps and the degree of improvement in vibration control performance;
2. The feasibility of calculating a predicted seismic wave for preview control is confirmed by using seismic wave data recorded by a seismograph set up several hundred meters below the ground surface; and
3. The feasibility of the preview control system is examined by predicting seismic waves that have errors caused by factors such as ground conditions.
Concerning point (1), a new formula is provided for calculating the controlling force by adding an optimum preview controlling force term to the formula using values observed by multipoint displacement measurement, which was described in Nakamura et al. (2010). Experiments and analyses are described for confirming the improvements in control performance accomplished by the addition of such an active preview control system.
Concerning point (2), whenever an earthquake occurs in Japan, the Earthquake Early Warning System provides advance warning of estimated seismic intensities and the time when the principal motion is expected to arrive. This system has been in operation around the country since 2007 (Megro and Fujinawa 2007; Fujita et al. 2011). These estimations are based on the prompt analyses using wave-form data observed by seismographs near the epicenter. This concept can be applied to a similar system that can anticipate seismic waves prior to their actual arrival time. One possible application, which is discussed in this paper, is to establish an active preview control system using data on predicted seismic wave behavior that has been formulated by applying an autoregressive model (Hannan 1970) in high speed computations on seismic wave data transmitted from a seismograph set up several hundred meters below the target structure. It is considered possible to predict seismic motion approximately 0.05–0.3 s prior to its occurrence at the ground surface by performing ground vibration analyses at extremely high-speeds. In previous computer methods (Lysmer and Kuhlemeyer 1969; Schnabel et al. 1972; Lysmer and Waas 1972; Lysmer et al. 1975), seismological models are used for analyzing the seismic response of soil structures and soil-structure interactions, resulting in the programs SHAKE, QUAD−4, FLUSH, and SASSI. These methods are not designed to predict future ground waves online. It is demonstrated how a predicted seismic wave at the ground surface can be calculated by using the underground observation data provided by the strong-motion seismograph network (National Research Institute for Earth Science and Disaster Prevention 1996), and the possibility of application to actual structures is examined.
Concerning point (3), the robustness of the active control system is examined when using predicted seismic wave data obtained by the one-dimensional wave propagation theory and it is compared to the case when using actual wave data observed at the ground surface. The ability of the control system to accommodate errors inherent in predicting seismic wave data is confirmed.
The proposed active preview control method is described in “Proposed Active Preview Control Method” section. The method for calculating a predicted seismic wave by analyzing KiK-net data is described in “Predicted Seismic Waves Using Autoregressive Model” section. In “Analysis of Preview Control Quality” section, it is described how predicted seismic waves can be applied to an active preview control system and how this can contribute to the robustness of the control system. The relation between the number of preview steps and the improvement of control performance is analytically examined.
Read More: http://ascelibrary.org/doi/10.1061/%28ASCE%29EM.1943-7889.0000979
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