Zhijun Zhu, Naoxi Dou, Kun Zheng, Yongli Lou, Bin Li, Yong Xiao
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引用次数: 0
Abstract
Active vibration isolation is widely recognized as an effective approach for suppressing low-frequency vibrations. Linear active disturbance rejection control (LADRC) serves as a powerful strategy for active vibration isolation. However, classic LADRC depends on displacement sensors, which are often bulky and prone to measurement instability. Substituting accelerometers for displacement sensors offers a promising alternative, as the former are generally more compact and provide superior measurement stability. Nevertheless, the integration of accelerometers into classic LADRC requires double integration to derive displacement, leading to low-frequency drift that may drive the system out of control. To overcome such limitation, this paper proposes a composite ADRC algorithm with a collaborative disturbance observer (CDO). The CDO integrates reduced-order LESO (RLESO) and Kalman filter (KF) in a complementary manner, which directly uses acceleration as input to avoid the risk of integral drift and realizes the functional complementarity between KF in state reconstruction and RLESO in disturbance estimation. Moreover, a composite scheme combining known-disturbance feedforward, unknown-disturbance feedback, and state errors feedback is adopted. Theory and experiments show that this method can achieve effective state reconstruction and disturbance suppression with only accelerometers while exhibiting good tolerance to small control-loop time delays, providing a streamlined and efficient solution for low-frequency broadband vibration isolation.
期刊介绍:
The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications.
Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics.
Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.