journal article·2024-10-18Open access

Research on a Bridge Hybrid Isolation Control System Based on PID Active Control and Genetic Algorithm Optimization

Ning Li, Ying Sheng, Wenjie Zheng, Zhenchao Yang, Zhonghai Zhang, Yanmei Li

Applied Sciences· Volume 14· Issue 20

Abstract

A bridge hybrid isolation system, integrating both active and passive control strategies, is proposed and investigated to enhance seismic performance. The system is modeled as a two-layer structure, with the upper layer subjected to active control via a Proportional–Integral–Derivative (PID) controller, and the lower layer employing a conventional passive base isolation system. The displacement response of the superstructure is minimized by the control forces generated by the PID controller, which also accounts for the reaction forces transmitted to the lower isolation layer. To optimize the controller’s performance, a genetic algorithm is implemented for real-time tuning of the PID parameters. Numerical simulations, conducted using the Newmark method, are employed to assess the influence of active control on the lower isolation system. The results reveal that, while active control increases the peak displacement of the superstructure to some extent, it significantly prolongs the structural period, thus enhancing the system’s overall seismic resilience and stability.
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Research context

OpenAlex topics: Elevator Systems and Control · Advanced Sensor and Control Systems · Hydraulic and Pneumatic Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang 621010, China

Shock and Vibration of Engineering Materials and Structures Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Mianyang 621010, China

Key Laboratory of Magnetic Molecules and Magnetic Information Materials of Ministry of Education, School of Chemistry and Materials Science, Shanxi Normal University, Taiyuan 030031, China

Funding

National Natural Science Foundation of China · Natural Science Foundation of Sichuan Province

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