Radial basis function neural network algorithm for semi‐active control of base‐isolated structures

• Published in: Structural control and health monitoring Vol. 24; no. 10; pp. e1984 - n/a
• Main Authors: Krishnamoorthy, Agrahara, Bhat, Shubha, Bhasari, Dattatreya
• Format: Journal Article
• Language: English
• Published: Pavia John Wiley & Sons, Inc 01.10.2017
• Subjects: Active control; Algorithms; base isolation; Computer simulation; control device; curved surface slider; Damping ratio; Earthquakes; Ground motion; Mathematical analysis; Neural networks; Radial basis function; radial basis function network; Seismic activity; Seismic engineering; Seismic isolation; Seismic response; variable orifice fluid damper
• ISSN: 1545-2255; 1545-2263
• DOI: 10.1002/stc.1984

Summary Curved surface slider (CSS) is considered as an effective isolation device for structures subjected to earthquake ground motions. Due to constant frequency, CSS may encounter a resonance problem when subjected to near‐fault earthquake ground motions. To overcome this problem, we propose CSS combined with a control device in this study. The control device consists of variable orifice fluid damper, and its damping coefficient is controlled by a radial basis function‐based neural network algorithm. Numerical simulations are performed to evaluate the effectiveness of the proposed technique for only one‐directional horizontal seismic excitations without any evaluation concerning the durability of CSSs. The results of the investigation demonstrate that the proposed technique is effective to reduce both the base shear and the sliding displacement of the isolated structure. In addition, the response predicted by the proposed technique is almost similar to the response of isolated structure with passive damper at optimum damping ratio.