Topic
Active vibration control
About: Active vibration control is a research topic. Over the lifetime, 6770 publications have been published within this topic receiving 76599 citations. The topic is also known as: active vibration damping.
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TL;DR: In this paper, a multi-start meta-heuristic algorithm called multiple start guided neighbourhood search (MSGNS) algorithm was proposed to find the optimal actuator locations in high-rise buildings.
25 citations
25 citations
TL;DR: In this paper, a method combining sliding mode control (SMC) and positive position feedback control (PPF) is proposed to suppress the vibration of the beam when the moving mass is on and off the beam.
25 citations
TL;DR: In this article, a visual sensor is used to measure the vibration of a piezoelectric flexible cantilever plate, and the measured signals are used as feedback to suppress the excited vibrations.
Abstract: A visual sensor is used to measure the vibration of a piezoelectric flexible cantilever plate. To decrease the image processing time and satisfy the requirement of real-time application, the searching range is limited by selecting region of interest images and using a tracking technique. After image processing, including median filter, image segmentation for object recognition, least squares technique, the vibrations of bending and torsional modes for flexible plate can be obtained. The visual measured signals are used as feedback to suppress the excited vibrations. The conventional proportional plus derivative (PD) control and finite-time control algorithms are designed and implemented. The experiments are conducted. The decoupling of measurement of the bending and torsional vibrations is realized by the visual sensor accompany with applying the image processing methods. Experimental results demonstrate that the designed control algorithm can suppress the low-frequency vibration effectively. Furthermore, the finite-time controller can damp out the small amplitude vibration much better than that of the PD control.
25 citations
TL;DR: The proposed heuristics approaches to reduce the unwanted structural response delivered due to the external excitation, namely, bull genetic algorithm and spiking neural network have outperformed other approaches.
Abstract: Systems with flexible structures display vibration as a characteristic property. However, when exposed to disturbing forces, then the component and/or structural nature of such systems are damaged. Therefore, this paper proposes two heuristics approaches to reduce the unwanted structural response delivered due to the external excitation; namely, bull genetic algorithm and spiking neural network. The bull genetic algorithm is based on a new selection property inherited from the bull concept. On the other hand, spiking neural network possess more than one synaptic terminal between each neural network layer and each synaptic terminal is modelled with a different period of delay. Extensive simulations have been conducted using simulated platform of a flexible beam vibration. To validate the proposed approaches, we performed a qualitative comparison with other related approaches such as traditional genetic algorithm, general regression neural network, bees algorithm, and adaptive neuro-fuzzy inference system. Based on the obtained results, it is found that the proposed approaches have outperformed other approaches, while bull genetic algorithm has a 5.2% performance improvement over spiking neural network.
25 citations